Multivariate Welch t-test on distances.

PubMed

Alekseyenko, Alexander V

2016-12-01

Permutational non-Euclidean analysis of variance, PERMANOVA, is routinely used in exploratory analysis of multivariate datasets to draw conclusions about the significance of patterns visualized through dimension reduction. This method recognizes that pairwise distance matrix between observations is sufficient to compute within and between group sums of squares necessary to form the (pseudo) F statistic. Moreover, not only Euclidean, but arbitrary distances can be used. This method, however, suffers from loss of power and type I error inflation in the presence of heteroscedasticity and sample size imbalances. We develop a solution in the form of a distance-based Welch t-test, [Formula: see text], for two sample potentially unbalanced and heteroscedastic data. We demonstrate empirically the desirable type I error and power characteristics of the new test. We compare the performance of PERMANOVA and [Formula: see text] in reanalysis of two existing microbiome datasets, where the methodology has originated. The source code for methods and analysis of this article is available at https://github.com/alekseyenko/Tw2 Further guidance on application of these methods can be obtained from the author. alekseye@musc.edu. © The Author 2016. Published by Oxford University Press.

Permutation Tests of Hierarchical Cluster Analyses of Carrion Communities and Their Potential Use in Forensic Entomology.

PubMed

van der Ham, Joris L

2016-05-19

Forensic entomologists can use carrion communities' ecological succession data to estimate the postmortem interval (PMI). Permutation tests of hierarchical cluster analyses of these data provide a conceptual method to estimate part of the PMI, the post-colonization interval (post-CI). This multivariate approach produces a baseline of statistically distinct clusters that reflect changes in the carrion community composition during the decomposition process. Carrion community samples of unknown post-CIs are compared with these baseline clusters to estimate the post-CI. In this short communication, I use data from previously published studies to demonstrate the conceptual feasibility of this multivariate approach. Analyses of these data produce series of significantly distinct clusters, which represent carrion communities during 1- to 20-day periods of the decomposition process. For 33 carrion community samples, collected over an 11-day period, this approach correctly estimated the post-CI within an average range of 3.1 days. © The Authors 2016. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Efficient Blockwise Permutation Tests Preserving Exchangeability

PubMed Central

Zhou, Chunxiao; Zwilling, Chris E.; Calhoun, Vince D.; Wang, Michelle Y.

2014-01-01

In this paper, we present a new blockwise permutation test approach based on the moments of the test statistic. The method is of importance to neuroimaging studies. In order to preserve the exchangeability condition required in permutation tests, we divide the entire set of data into certain exchangeability blocks. In addition, computationally efficient moments-based permutation tests are performed by approximating the permutation distribution of the test statistic with the Pearson distribution series. This involves the calculation of the first four moments of the permutation distribution within each block and then over the entire set of data. The accuracy and efficiency of the proposed method are demonstrated through simulated experiment on the magnetic resonance imaging (MRI) brain data, specifically the multi-site voxel-based morphometry analysis from structural MRI (sMRI). PMID:25289113

Alignment-Independent Comparisons of Human Gastrointestinal Tract Microbial Communities in a Multidimensional 16S rRNA Gene Evolutionary Space▿

PubMed Central

Rudi, Knut; Zimonja, Monika; Kvenshagen, Bente; Rugtveit, Jarle; Midtvedt, Tore; Eggesbø, Merete

2007-01-01

We present a novel approach for comparing 16S rRNA gene clone libraries that is independent of both DNA sequence alignment and definition of bacterial phylogroups. These steps are the major bottlenecks in current microbial comparative analyses. We used direct comparisons of taxon density distributions in an absolute evolutionary coordinate space. The coordinate space was generated by using alignment-independent bilinear multivariate modeling. Statistical analyses for clone library comparisons were based on multivariate analysis of variance, partial least-squares regression, and permutations. Clone libraries from both adult and infant gastrointestinal tract microbial communities were used as biological models. We reanalyzed a library consisting of 11,831 clones covering complete colons from three healthy adults in addition to a smaller 390-clone library from infant feces. We show that it is possible to extract detailed information about microbial community structures using our alignment-independent method. Our density distribution analysis is also very efficient with respect to computer operation time, meeting the future requirements of large-scale screenings to understand the diversity and dynamics of microbial communities. PMID:17337554

Identifying ADHD children using hemodynamic responses during a working memory task measured by functional near-infrared spectroscopy.

PubMed

Gu, Yue; Miao, Shuo; Han, Junxia; Liang, Zhenhu; Ouyang, Gaoxiang; Yang, Jian; Li, Xiaoli

2018-06-01

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting children and adults. Previous studies found that functional near-infrared spectroscopy (fNIRS) can reveal significant group differences in several brain regions between ADHD children and healthy controls during working memory tasks. This study aimed to use fNIRS activation patterns to identify ADHD children from healthy controls. FNIRS signals from 25 ADHD children and 25 healthy controls performing the n-back task were recorded; then, multivariate pattern analysis was used to discriminate ADHD individuals from healthy controls, and classification performance was evaluated for significance by the permutation test. The results showed that 86.0% ([Formula: see text]) of participants can be correctly classified in leave-one-out cross-validation. The most discriminative brain regions included the bilateral dorsolateral prefrontal cortex, inferior medial prefrontal cortex, right posterior prefrontal cortex, and right temporal cortex. This study demonstrated that, in a small sample, multivariate pattern analysis can effectively identify ADHD children from healthy controls based on fNIRS signals, which argues for the potential utility of fNIRS in future assessments.

Frequency-domain-independent vector analysis for mode-division multiplexed transmission

NASA Astrophysics Data System (ADS)

Liu, Yunhe; Hu, Guijun; Li, Jiao

2018-04-01

In this paper, we propose a demultiplexing method based on frequency-domain independent vector analysis (FD-IVA) algorithm for mode-division multiplexing (MDM) system. FD-IVA extends frequency-domain independent component analysis (FD-ICA) from unitary variable to multivariate variables, and provides an efficient method to eliminate the permutation ambiguity. In order to verify the performance of FD-IVA algorithm, a 6 ×6 MDM system is simulated. The simulation results show that the FD-IVA algorithm has basically the same bit-error-rate(BER) performance with the FD-ICA algorithm and frequency-domain least mean squares (FD-LMS) algorithm. Meanwhile, the convergence speed of FD-IVA algorithm is the same as that of FD-ICA. However, compared with the FD-ICA and the FD-LMS, the FD-IVA has an obviously lower computational complexity.

Global spectral graph wavelet signature for surface analysis of carpal bones

NASA Astrophysics Data System (ADS)

Masoumi, Majid; Rezaei, Mahsa; Ben Hamza, A.

2018-02-01

Quantitative shape comparison is a fundamental problem in computer vision, geometry processing and medical imaging. In this paper, we present a spectral graph wavelet approach for shape analysis of carpal bones of the human wrist. We employ spectral graph wavelets to represent the cortical surface of a carpal bone via the spectral geometric analysis of the Laplace-Beltrami operator in the discrete domain. We propose global spectral graph wavelet (GSGW) descriptor that is isometric invariant, efficient to compute, and combines the advantages of both low-pass and band-pass filters. We perform experiments on shapes of the carpal bones of ten women and ten men from a publicly-available database of wrist bones. Using one-way multivariate analysis of variance (MANOVA) and permutation testing, we show through extensive experiments that the proposed GSGW framework gives a much better performance compared to the global point signature embedding approach for comparing shapes of the carpal bones across populations.

Global spectral graph wavelet signature for surface analysis of carpal bones.

PubMed

Masoumi, Majid; Rezaei, Mahsa; Ben Hamza, A

2018-02-05

Quantitative shape comparison is a fundamental problem in computer vision, geometry processing and medical imaging. In this paper, we present a spectral graph wavelet approach for shape analysis of carpal bones of the human wrist. We employ spectral graph wavelets to represent the cortical surface of a carpal bone via the spectral geometric analysis of the Laplace-Beltrami operator in the discrete domain. We propose global spectral graph wavelet (GSGW) descriptor that is isometric invariant, efficient to compute, and combines the advantages of both low-pass and band-pass filters. We perform experiments on shapes of the carpal bones of ten women and ten men from a publicly-available database of wrist bones. Using one-way multivariate analysis of variance (MANOVA) and permutation testing, we show through extensive experiments that the proposed GSGW framework gives a much better performance compared to the global point signature embedding approach for comparing shapes of the carpal bones across populations.

Visual recognition of permuted words

NASA Astrophysics Data System (ADS)

Rashid, Sheikh Faisal; Shafait, Faisal; Breuel, Thomas M.

2010-02-01

In current study we examine how letter permutation affects in visual recognition of words for two orthographically dissimilar languages, Urdu and German. We present the hypothesis that recognition or reading of permuted and non-permuted words are two distinct mental level processes, and that people use different strategies in handling permuted words as compared to normal words. A comparison between reading behavior of people in these languages is also presented. We present our study in context of dual route theories of reading and it is observed that the dual-route theory is consistent with explanation of our hypothesis of distinction in underlying cognitive behavior for reading permuted and non-permuted words. We conducted three experiments in lexical decision tasks to analyze how reading is degraded or affected by letter permutation. We performed analysis of variance (ANOVA), distribution free rank test, and t-test to determine the significance differences in response time latencies for two classes of data. Results showed that the recognition accuracy for permuted words is decreased 31% in case of Urdu and 11% in case of German language. We also found a considerable difference in reading behavior for cursive and alphabetic languages and it is observed that reading of Urdu is comparatively slower than reading of German due to characteristics of cursive script.

A Permutation Approach for Selecting the Penalty Parameter in Penalized Model Selection

PubMed Central

Sabourin, Jeremy A; Valdar, William; Nobel, Andrew B

2015-01-01

Summary We describe a simple, computationally effcient, permutation-based procedure for selecting the penalty parameter in LASSO penalized regression. The procedure, permutation selection, is intended for applications where variable selection is the primary focus, and can be applied in a variety of structural settings, including that of generalized linear models. We briefly discuss connections between permutation selection and existing theory for the LASSO. In addition, we present a simulation study and an analysis of real biomedical data sets in which permutation selection is compared with selection based on the following: cross-validation (CV), the Bayesian information criterion (BIC), Scaled Sparse Linear Regression, and a selection method based on recently developed testing procedures for the LASSO. PMID:26243050

Toward a general theory of conical intersections in systems of identical nuclei

NASA Astrophysics Data System (ADS)

Keating, Sean P.; Mead, C. Alden

1987-02-01

It has been shown previously that the Herzberg-Longuet-Higgins sign change produced in Born-Oppenheimer electronic wave functions when the nuclei traverse a closed path around a conical intersection has implications for the symmetry of wave functions under permutations of identical nuclei. For systems of three or four identical nuclei, there are special features present which have facilitated the detailed analysis. The present paper reports progress toward a general theory for systems of n nuclei. For n=3 or 4, the two key functions which locate conical intersections and define compensating phase factors can conveniently be defined so as to transform under permutations according to a two-dimensional irreducible representation of the permutation group. Since such representations do not exist for n>4, we have chosen to develop a formalism in terms of lab-fixed electronic basis functions, and we show how to define the two key functions in principle. The functions so defined both turn out to be totally symmetric under permutations. We show how they can be used to define compensating phase factors so that all modified electronic wave functions are either totally symmetric or totally antisymmetric under permutations. A detailed analysis is made to cyclic permutations in the neighborhood of Dnh symmetry, which can be extended by continuity arguments to more general configurations, and criteria are obtained for sign changes. There is a qualitative discussion of the treatment of more general permutations.

A Comparison of Multiscale Permutation Entropy Measures in On-Line Depth of Anesthesia Monitoring.

PubMed

Su, Cui; Liang, Zhenhu; Li, Xiaoli; Li, Duan; Li, Yongwang; Ursino, Mauro

2016-01-01

Multiscale permutation entropy (MSPE) is becoming an interesting tool to explore neurophysiological mechanisms in recent years. In this study, six MSPE measures were proposed for on-line depth of anesthesia (DoA) monitoring to quantify the anesthetic effect on the real-time EEG recordings. The performance of these measures in describing the transient characters of simulated neural populations and clinical anesthesia EEG were evaluated and compared. Six MSPE algorithms-derived from Shannon permutation entropy (SPE), Renyi permutation entropy (RPE) and Tsallis permutation entropy (TPE) combined with the decomposition procedures of coarse-graining (CG) method and moving average (MA) analysis-were studied. A thalamo-cortical neural mass model (TCNMM) was used to generate noise-free EEG under anesthesia to quantitatively assess the robustness of each MSPE measure against noise. Then, the clinical anesthesia EEG recordings from 20 patients were analyzed with these measures. To validate their effectiveness, the ability of six measures were compared in terms of tracking the dynamical changes in EEG data and the performance in state discrimination. The Pearson correlation coefficient (R) was used to assess the relationship among MSPE measures. CG-based MSPEs failed in on-line DoA monitoring at multiscale analysis. In on-line EEG analysis, the MA-based MSPE measures at 5 decomposed scales could track the transient changes of EEG recordings and statistically distinguish the awake state, unconsciousness and recovery of consciousness (RoC) state significantly. Compared to single-scale SPE and RPE, MSPEs had better anti-noise ability and MA-RPE at scale 5 performed best in this aspect. MA-TPE outperformed other measures with faster tracking speed of the loss of unconsciousness. MA-based multiscale permutation entropies have the potential for on-line anesthesia EEG analysis with its simple computation and sensitivity to drug effect changes. CG-based multiscale permutation entropies may fail to describe the characteristics of EEG at high decomposition scales.

Instability of Hierarchical Cluster Analysis Due to Input Order of the Data: The PermuCLUSTER Solution

ERIC Educational Resources Information Center

van der Kloot, Willem A.; Spaans, Alexander M. J.; Heiser, Willem J.

2005-01-01

Hierarchical agglomerative cluster analysis (HACA) may yield different solutions under permutations of the input order of the data. This instability is caused by ties, either in the initial proximity matrix or arising during agglomeration. The authors recommend to repeat the analysis on a large number of random permutations of the rows and columns…

Heuristic Implementation of Dynamic Programming for Matrix Permutation Problems in Combinatorial Data Analysis

ERIC Educational Resources Information Center

Brusco, Michael J.; Kohn, Hans-Friedrich; Stahl, Stephanie

2008-01-01

Dynamic programming methods for matrix permutation problems in combinatorial data analysis can produce globally-optimal solutions for matrices up to size 30x30, but are computationally infeasible for larger matrices because of enormous computer memory requirements. Branch-and-bound methods also guarantee globally-optimal solutions, but computation…

Photospheric Magnetic Field Properties of Flaring versus Flare-quiet Active Regions. II. Discriminant Analysis

NASA Astrophysics Data System (ADS)

Leka, K. D.; Barnes, G.

2003-10-01

We apply statistical tests based on discriminant analysis to the wide range of photospheric magnetic parameters described in a companion paper by Leka & Barnes, with the goal of identifying those properties that are important for the production of energetic events such as solar flares. The photospheric vector magnetic field data from the University of Hawai'i Imaging Vector Magnetograph are well sampled both temporally and spatially, and we include here data covering 24 flare-event and flare-quiet epochs taken from seven active regions. The mean value and rate of change of each magnetic parameter are treated as separate variables, thus evaluating both the parameter's state and its evolution, to determine which properties are associated with flaring. Considering single variables first, Hotelling's T2-tests show small statistical differences between flare-producing and flare-quiet epochs. Even pairs of variables considered simultaneously, which do show a statistical difference for a number of properties, have high error rates, implying a large degree of overlap of the samples. To better distinguish between flare-producing and flare-quiet populations, larger numbers of variables are simultaneously considered; lower error rates result, but no unique combination of variables is clearly the best discriminator. The sample size is too small to directly compare the predictive power of large numbers of variables simultaneously. Instead, we rank all possible four-variable permutations based on Hotelling's T2-test and look for the most frequently appearing variables in the best permutations, with the interpretation that they are most likely to be associated with flaring. These variables include an increasing kurtosis of the twist parameter and a larger standard deviation of the twist parameter, but a smaller standard deviation of the distribution of the horizontal shear angle and a horizontal field that has a smaller standard deviation but a larger kurtosis. To support the ``sorting all permutations'' method of selecting the most frequently occurring variables, we show that the results of a single 10-variable discriminant analysis are consistent with the ranking. We demonstrate that individually, the variables considered here have little ability to differentiate between flaring and flare-quiet populations, but with multivariable combinations, the populations may be distinguished.

Identifying ADHD children using hemodynamic responses during a working memory task measured by functional near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Gu, Yue; Miao, Shuo; Han, Junxia; Liang, Zhenhu; Ouyang, Gaoxiang; Yang, Jian; Li, Xiaoli

2018-06-01

Objective. Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder affecting children and adults. Previous studies found that functional near-infrared spectroscopy (fNIRS) can reveal significant group differences in several brain regions between ADHD children and healthy controls during working memory tasks. This study aimed to use fNIRS activation patterns to identify ADHD children from healthy controls. Approach. FNIRS signals from 25 ADHD children and 25 healthy controls performing the n-back task were recorded; then, multivariate pattern analysis was used to discriminate ADHD individuals from healthy controls, and classification performance was evaluated for significance by the permutation test. Main results. The results showed that 86.0% (p<0.001 ) of participants can be correctly classified in leave-one-out cross-validation. The most discriminative brain regions included the bilateral dorsolateral prefrontal cortex, inferior medial prefrontal cortex, right posterior prefrontal cortex, and right temporal cortex. Significance. This study demonstrated that, in a small sample, multivariate pattern analysis can effectively identify ADHD children from healthy controls based on fNIRS signals, which argues for the potential utility of fNIRS in future assessments.

Altering the orientation of a fused protein to the RNA-binding ribosomal protein L7Ae and its derivatives through circular permutation.

PubMed

Ohuchi, Shoji J; Sagawa, Fumihiko; Sakamoto, Taiichi; Inoue, Tan

2015-10-23

RNA-protein complexes (RNPs) are useful for constructing functional nano-objects because a variety of functional proteins can be displayed on a designed RNA scaffold. Here, we report circular permutations of an RNA-binding protein L7Ae based on the three-dimensional structure information to alter the orientation of the displayed proteins on the RNA scaffold. An electrophoretic mobility shift assay and atomic force microscopy (AFM) analysis revealed that most of the designed circular permutants formed an RNP nano-object. Moreover, the alteration of the enhanced green fluorescent protein (EGFP) orientation was confirmed with AFM by employing EGFP on the L7Ae permutant on the RNA. The results demonstrate that targeted fine-tuning of the stereo-specific fixation of a protein on a protein-binding RNA is feasible by using the circular permutation technique. Copyright © 2015 Elsevier Inc. All rights reserved.

Altering the orientation of a fused protein to the RNA-binding ribosomal protein L7Ae and its derivatives through circular permutation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ohuchi, Shoji J.; Sagawa, Fumihiko; Sakamoto, Taiichi

RNA-protein complexes (RNPs) are useful for constructing functional nano-objects because a variety of functional proteins can be displayed on a designed RNA scaffold. Here, we report circular permutations of an RNA-binding protein L7Ae based on the three-dimensional structure information to alter the orientation of the displayed proteins on the RNA scaffold. An electrophoretic mobility shift assay and atomic force microscopy (AFM) analysis revealed that most of the designed circular permutants formed an RNP nano-object. Moreover, the alteration of the enhanced green fluorescent protein (EGFP) orientation was confirmed with AFM by employing EGFP on the L7Ae permutant on the RNA. Themore » results demonstrate that targeted fine-tuning of the stereo-specific fixation of a protein on a protein-binding RNA is feasible by using the circular permutation technique.« less

A Comparison of Multiscale Permutation Entropy Measures in On-Line Depth of Anesthesia Monitoring

PubMed Central

Li, Xiaoli; Li, Duan; Li, Yongwang; Ursino, Mauro

2016-01-01

Objective Multiscale permutation entropy (MSPE) is becoming an interesting tool to explore neurophysiological mechanisms in recent years. In this study, six MSPE measures were proposed for on-line depth of anesthesia (DoA) monitoring to quantify the anesthetic effect on the real-time EEG recordings. The performance of these measures in describing the transient characters of simulated neural populations and clinical anesthesia EEG were evaluated and compared. Methods Six MSPE algorithms—derived from Shannon permutation entropy (SPE), Renyi permutation entropy (RPE) and Tsallis permutation entropy (TPE) combined with the decomposition procedures of coarse-graining (CG) method and moving average (MA) analysis—were studied. A thalamo-cortical neural mass model (TCNMM) was used to generate noise-free EEG under anesthesia to quantitatively assess the robustness of each MSPE measure against noise. Then, the clinical anesthesia EEG recordings from 20 patients were analyzed with these measures. To validate their effectiveness, the ability of six measures were compared in terms of tracking the dynamical changes in EEG data and the performance in state discrimination. The Pearson correlation coefficient (R) was used to assess the relationship among MSPE measures. Results CG-based MSPEs failed in on-line DoA monitoring at multiscale analysis. In on-line EEG analysis, the MA-based MSPE measures at 5 decomposed scales could track the transient changes of EEG recordings and statistically distinguish the awake state, unconsciousness and recovery of consciousness (RoC) state significantly. Compared to single-scale SPE and RPE, MSPEs had better anti-noise ability and MA-RPE at scale 5 performed best in this aspect. MA-TPE outperformed other measures with faster tracking speed of the loss of unconsciousness. Conclusions MA-based multiscale permutation entropies have the potential for on-line anesthesia EEG analysis with its simple computation and sensitivity to drug effect changes. CG-based multiscale permutation entropies may fail to describe the characteristics of EEG at high decomposition scales. PMID:27723803

Permutation Entropy and Signal Energy Increase the Accuracy of Neuropathic Change Detection in Needle EMG

PubMed Central

2018-01-01

Background and Objective. Needle electromyography can be used to detect the number of changes and morphological changes in motor unit potentials of patients with axonal neuropathy. General mathematical methods of pattern recognition and signal analysis were applied to recognize neuropathic changes. This study validates the possibility of extending and refining turns-amplitude analysis using permutation entropy and signal energy. Methods. In this study, we examined needle electromyography in 40 neuropathic individuals and 40 controls. The number of turns, amplitude between turns, signal energy, and “permutation entropy” were used as features for support vector machine classification. Results. The obtained results proved the superior classification performance of the combinations of all of the above-mentioned features compared to the combinations of fewer features. The lowest accuracy from the tested combinations of features had peak-ratio analysis. Conclusion. Using the combination of permutation entropy with signal energy, number of turns and mean amplitude in SVM classification can be used to refine the diagnosis of polyneuropathies examined by needle electromyography. PMID:29606959

Estrogen pathway polymorphisms in relation to primary open angle glaucoma: An analysis accounting for gender from the United States

PubMed Central

Loomis, Stephanie J.; Weinreb, Robert N.; Kang, Jae H.; Yaspan, Brian L.; Bailey, Jessica Cooke; Gaasterland, Douglas; Gaasterland, Terry; Lee, Richard K.; Scott, William K.; Lichter, Paul R.; Budenz, Donald L.; Liu, Yutao; Realini, Tony; Friedman, David S.; McCarty, Catherine A.; Moroi, Sayoko E.; Olson, Lana; Schuman, Joel S.; Singh, Kuldev; Vollrath, Douglas; Wollstein, Gadi; Zack, Donald J.; Brilliant, Murray; Sit, Arthur J.; Christen, William G.; Fingert, John; Kraft, Peter; Zhang, Kang; Allingham, R. Rand; Pericak-Vance, Margaret A.; Richards, Julia E.; Hauser, Michael A.; Haines, Jonathan L.; Wiggs, Janey L.

2013-01-01

Purpose Circulating estrogen levels are relevant in glaucoma phenotypic traits. We assessed the association between an estrogen metabolism single nucleotide polymorphism (SNP) panel in relation to primary open angle glaucoma (POAG), accounting for gender. Methods We included 3,108 POAG cases and 3,430 controls of both genders from the Glaucoma Genes and Environment (GLAUGEN) study and the National Eye Institute Glaucoma Human Genetics Collaboration (NEIGHBOR) consortium genotyped on the Illumina 660W-Quad platform. We assessed the relation between the SNP panels representative of estrogen metabolism and POAG using pathway- and gene-based approaches with the Pathway Analysis by Randomization Incorporating Structure (PARIS) software. PARIS executes a permutation algorithm to assess statistical significance relative to the pathways and genes of comparable genetic architecture. These analyses were performed using the meta-analyzed results from the GLAUGEN and NEIGHBOR data sets. We evaluated POAG overall as well as two subtypes of POAG defined as intraocular pressure (IOP) ≥22 mmHg (high-pressure glaucoma [HPG]) or IOP <22 mmHg (normal pressure glaucoma [NPG]) at diagnosis. We conducted these analyses for each gender separately and then jointly in men and women. Results Among women, the estrogen SNP pathway was associated with POAG overall (permuted p=0.006) and HPG (permuted p<0.001) but not NPG (permuted p=0.09). Interestingly, there was no relation between the estrogen SNP pathway and POAG when men were considered alone (permuted p>0.99). Among women, gene-based analyses revealed that the catechol-O-methyltransferase gene showed strong associations with HTG (permuted gene p≤0.001) and NPG (permuted gene p=0.01). Conclusions The estrogen SNP pathway was associated with POAG among women. PMID:23869166

Statistical significance approximation in local trend analysis of high-throughput time-series data using the theory of Markov chains.

PubMed

Xia, Li C; Ai, Dongmei; Cram, Jacob A; Liang, Xiaoyi; Fuhrman, Jed A; Sun, Fengzhu

2015-09-21

Local trend (i.e. shape) analysis of time series data reveals co-changing patterns in dynamics of biological systems. However, slow permutation procedures to evaluate the statistical significance of local trend scores have limited its applications to high-throughput time series data analysis, e.g., data from the next generation sequencing technology based studies. By extending the theories for the tail probability of the range of sum of Markovian random variables, we propose formulae for approximating the statistical significance of local trend scores. Using simulations and real data, we show that the approximate p-value is close to that obtained using a large number of permutations (starting at time points >20 with no delay and >30 with delay of at most three time steps) in that the non-zero decimals of the p-values obtained by the approximation and the permutations are mostly the same when the approximate p-value is less than 0.05. In addition, the approximate p-value is slightly larger than that based on permutations making hypothesis testing based on the approximate p-value conservative. The approximation enables efficient calculation of p-values for pairwise local trend analysis, making large scale all-versus-all comparisons possible. We also propose a hybrid approach by integrating the approximation and permutations to obtain accurate p-values for significantly associated pairs. We further demonstrate its use with the analysis of the Polymouth Marine Laboratory (PML) microbial community time series from high-throughput sequencing data and found interesting organism co-occurrence dynamic patterns. The software tool is integrated into the eLSA software package that now provides accelerated local trend and similarity analysis pipelines for time series data. The package is freely available from the eLSA website: http://bitbucket.org/charade/elsa.

Multivariate and repeated measures (MRM): A new toolbox for dependent and multimodal group-level neuroimaging data

PubMed Central

McFarquhar, Martyn; McKie, Shane; Emsley, Richard; Suckling, John; Elliott, Rebecca; Williams, Stephen

2016-01-01

Repeated measurements and multimodal data are common in neuroimaging research. Despite this, conventional approaches to group level analysis ignore these repeated measurements in favour of multiple between-subject models using contrasts of interest. This approach has a number of drawbacks as certain designs and comparisons of interest are either not possible or complex to implement. Unfortunately, even when attempting to analyse group level data within a repeated-measures framework, the methods implemented in popular software packages make potentially unrealistic assumptions about the covariance structure across the brain. In this paper, we describe how this issue can be addressed in a simple and efficient manner using the multivariate form of the familiar general linear model (GLM), as implemented in a new MATLAB toolbox. This multivariate framework is discussed, paying particular attention to methods of inference by permutation. Comparisons with existing approaches and software packages for dependent group-level neuroimaging data are made. We also demonstrate how this method is easily adapted for dependency at the group level when multiple modalities of imaging are collected from the same individuals. Follow-up of these multimodal models using linear discriminant functions (LDA) is also discussed, with applications to future studies wishing to integrate multiple scanning techniques into investigating populations of interest. PMID:26921716

Effects of smallmouth buffalo, Ictiobus bubalus biomass on water transparency, nutrients, and productivity in shallow experimental ponds

USGS Publications Warehouse

Goetz, Daniel B.; Kroger, Robert; Miranda, Leandro E.

2014-01-01

The smallmouth buffalo Ictiobus bubalus is a native benthivore to floodplain lakes in the Yazoo River Basin, USA. Based on evidence from other benthivorous fish studies we hypothesized high biomasses of I. bubalus contribute to poor water quality conditions. We tested this hypothesis in shallow (< 1.5 m) 0.05 ha earthen ponds at three stocking biomasses over a 10-week period during the summer of 2012. The most notable results from the permutational multivariate analysis of variance suggest I. bubalus at high and moderate biomasses significantly (p < 0.05) enhanced turbidity and suspended solid levels while decreasing Secchi depth. Our results suggest that effects of I. bubalus on water clarity may have considerable ecological implications in natural habitats such as shallow floodplain lakes.

Automatic event detection in low SNR microseismic signals based on multi-scale permutation entropy and a support vector machine

NASA Astrophysics Data System (ADS)

Jia, Rui-Sheng; Sun, Hong-Mei; Peng, Yan-Jun; Liang, Yong-Quan; Lu, Xin-Ming

2017-07-01

Microseismic monitoring is an effective means for providing early warning of rock or coal dynamical disasters, and its first step is microseismic event detection, although low SNR microseismic signals often cannot effectively be detected by routine methods. To solve this problem, this paper presents permutation entropy and a support vector machine to detect low SNR microseismic events. First, an extraction method of signal features based on multi-scale permutation entropy is proposed by studying the influence of the scale factor on the signal permutation entropy. Second, the detection model of low SNR microseismic events based on the least squares support vector machine is built by performing a multi-scale permutation entropy calculation for the collected vibration signals, constructing a feature vector set of signals. Finally, a comparative analysis of the microseismic events and noise signals in the experiment proves that the different characteristics of the two can be fully expressed by using multi-scale permutation entropy. The detection model of microseismic events combined with the support vector machine, which has the features of high classification accuracy and fast real-time algorithms, can meet the requirements of online, real-time extractions of microseismic events.

Physical Connectivity Mapping by Circular Permutation of Human Telomerase RNA Reveals New Regions Critical for Activity and Processivity.

PubMed

Mefford, Melissa A; Zappulla, David C

2016-01-15

Telomerase is a specialized ribonucleoprotein complex that extends the 3' ends of chromosomes to counteract telomere shortening. However, increased telomerase activity is associated with ∼90% of human cancers. The telomerase enzyme minimally requires an RNA (hTR) and a specialized reverse transcriptase protein (TERT) for activity in vitro. Understanding the structure-function relationships within hTR has important implications for human disease. For the first time, we have tested the physical-connectivity requirements in the 451-nucleotide hTR RNA using circular permutations, which reposition the 5' and 3' ends. Our extensive in vitro analysis identified three classes of hTR circular permutants with altered function. First, circularly permuting 3' of the template causes specific defects in repeat-addition processivity, revealing that the template recognition element found in ciliates is conserved in human telomerase RNA. Second, seven circular permutations residing within the catalytically important core and CR4/5 domains completely abolish telomerase activity, unveiling mechanistically critical portions of these domains. Third, several circular permutations between the core and CR4/5 significantly increase telomerase activity. Our extensive circular permutation results provide insights into the architecture and coordination of human telomerase RNA and highlight where the RNA could be targeted for the development of antiaging and anticancer therapeutics. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Physical Connectivity Mapping by Circular Permutation of Human Telomerase RNA Reveals New Regions Critical for Activity and Processivity

PubMed Central

Mefford, Melissa A.

2015-01-01

Telomerase is a specialized ribonucleoprotein complex that extends the 3′ ends of chromosomes to counteract telomere shortening. However, increased telomerase activity is associated with ∼90% of human cancers. The telomerase enzyme minimally requires an RNA (hTR) and a specialized reverse transcriptase protein (TERT) for activity in vitro. Understanding the structure-function relationships within hTR has important implications for human disease. For the first time, we have tested the physical-connectivity requirements in the 451-nucleotide hTR RNA using circular permutations, which reposition the 5′ and 3′ ends. Our extensive in vitro analysis identified three classes of hTR circular permutants with altered function. First, circularly permuting 3′ of the template causes specific defects in repeat-addition processivity, revealing that the template recognition element found in ciliates is conserved in human telomerase RNA. Second, seven circular permutations residing within the catalytically important core and CR4/5 domains completely abolish telomerase activity, unveiling mechanistically critical portions of these domains. Third, several circular permutations between the core and CR4/5 significantly increase telomerase activity. Our extensive circular permutation results provide insights into the architecture and coordination of human telomerase RNA and highlight where the RNA could be targeted for the development of antiaging and anticancer therapeutics. PMID:26503788

Parasite fauna of Etheostoma nigrum (Percidae: Etheostomatinae) in localities of varying pollution stress in the St. Lawrence River, Quebec, Canada.

PubMed

Krause, Rachel J; McLaughlin, J Daniel; Marcogliese, David J

2010-07-01

Parasite communities were examined in johnny darters (Etheostoma nigrum) collected from five localities in the St. Lawrence River in southwestern Quebec: two reference localities, one polluted locality upstream of the Island of Montreal and downstream of industrial and agricultural activity, and two polluted localities downstream of the Island of Montreal in the plume from the wastewater treatment facility. Twenty-four helminth species were found. Fish from the upstream polluted locality had the highest parasite species richness and total parasite numbers, and fish from the downstream polluted localities the lowest. Nonmetric multivariate analyses were conducted using square-root-transformed Bray-Curtis dissimilarity index. An analysis of similarity, dendrogram of centroids, and a permutational multivariate analysis of variance with contrasts all showed that fish from the reference localities had different parasite community composition than those from the polluted localities, and fish from the upstream polluted locality had different parasite communities than fish from the downstream polluted localities. Differences between reference and polluted localities were mainly due to higher abundances of the brain-encysting trematode, Ornithodiplostomum sp., at the reference localities. Differences between upstream and downstream polluted localities were mainly due to a higher diversity and abundance of trematodes in fish at the upstream locality.

Multi-scale symbolic transfer entropy analysis of EEG

NASA Astrophysics Data System (ADS)

Yao, Wenpo; Wang, Jun

2017-10-01

From both global and local perspectives, we symbolize two kinds of EEG and analyze their dynamic and asymmetrical information using multi-scale transfer entropy. Multi-scale process with scale factor from 1 to 199 and step size of 2 is applied to EEG of healthy people and epileptic patients, and then the permutation with embedding dimension of 3 and global approach are used to symbolize the sequences. The forward and reverse symbol sequences are taken as the inputs of transfer entropy. Scale factor intervals of permutation and global way are (37, 57) and (65, 85) where the two kinds of EEG have satisfied entropy distinctions. When scale factor is 67, transfer entropy of the healthy and epileptic subjects of permutation, 0.1137 and 0.1028, have biggest difference. And the corresponding values of the global symbolization is 0.0641 and 0.0601 which lies in the scale factor of 165. Research results show that permutation which takes contribution of local information has better distinction and is more effectively applied to our multi-scale transfer entropy analysis of EEG.

A new EEG synchronization strength analysis method: S-estimator based normalized weighted-permutation mutual information.

PubMed

Cui, Dong; Pu, Weiting; Liu, Jing; Bian, Zhijie; Li, Qiuli; Wang, Lei; Gu, Guanghua

2016-10-01

Synchronization is an important mechanism for understanding information processing in normal or abnormal brains. In this paper, we propose a new method called normalized weighted-permutation mutual information (NWPMI) for double variable signal synchronization analysis and combine NWPMI with S-estimator measure to generate a new method named S-estimator based normalized weighted-permutation mutual information (SNWPMI) for analyzing multi-channel electroencephalographic (EEG) synchronization strength. The performances including the effects of time delay, embedding dimension, coupling coefficients, signal to noise ratios (SNRs) and data length of the NWPMI are evaluated by using Coupled Henon mapping model. The results show that the NWPMI is superior in describing the synchronization compared with the normalized permutation mutual information (NPMI). Furthermore, the proposed SNWPMI method is applied to analyze scalp EEG data from 26 amnestic mild cognitive impairment (aMCI) subjects and 20 age-matched controls with normal cognitive function, who both suffer from type 2 diabetes mellitus (T2DM). The proposed methods NWPMI and SNWPMI are suggested to be an effective index to estimate the synchronization strength. Copyright © 2016 Elsevier Ltd. All rights reserved.

Effects of smallmouth buffalo, Ictiobus bubalus biomass on water transparency, nutrients, and productivity in shallow experimental ponds.

PubMed

Goetz, D; Kröger, R; Miranda, L E

2014-05-01

The smallmouth buffalo Ictiobus bubalus is a native benthivore to floodplain lakes in the Yazoo River Basin, USA. Based on evidence from other benthivorous fish studies we hypothesized high biomasses of I. bubalus contribute to poor water quality conditions. We tested this hypothesis in shallow (<1.5 m) 0.05 ha earthen ponds at three stocking biomasses over a 10-week period during the summer of 2012. The most notable results from the permutational multivariate analysis of variance suggest I. bubalus at high and moderate biomasses significantly (p < 0.05) enhanced turbidity and suspended solid levels while decreasing Secchi depth. Our results suggest that effects of I. bubalus on water clarity may have considerable ecological implications in natural habitats such as shallow floodplain lakes.

Multivariate and repeated measures (MRM): A new toolbox for dependent and multimodal group-level neuroimaging data.

PubMed

McFarquhar, Martyn; McKie, Shane; Emsley, Richard; Suckling, John; Elliott, Rebecca; Williams, Stephen

2016-05-15

Repeated measurements and multimodal data are common in neuroimaging research. Despite this, conventional approaches to group level analysis ignore these repeated measurements in favour of multiple between-subject models using contrasts of interest. This approach has a number of drawbacks as certain designs and comparisons of interest are either not possible or complex to implement. Unfortunately, even when attempting to analyse group level data within a repeated-measures framework, the methods implemented in popular software packages make potentially unrealistic assumptions about the covariance structure across the brain. In this paper, we describe how this issue can be addressed in a simple and efficient manner using the multivariate form of the familiar general linear model (GLM), as implemented in a new MATLAB toolbox. This multivariate framework is discussed, paying particular attention to methods of inference by permutation. Comparisons with existing approaches and software packages for dependent group-level neuroimaging data are made. We also demonstrate how this method is easily adapted for dependency at the group level when multiple modalities of imaging are collected from the same individuals. Follow-up of these multimodal models using linear discriminant functions (LDA) is also discussed, with applications to future studies wishing to integrate multiple scanning techniques into investigating populations of interest. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Gene set analysis using variance component tests.

PubMed

Huang, Yen-Tsung; Lin, Xihong

2013-06-28

Gene set analyses have become increasingly important in genomic research, as many complex diseases are contributed jointly by alterations of numerous genes. Genes often coordinate together as a functional repertoire, e.g., a biological pathway/network and are highly correlated. However, most of the existing gene set analysis methods do not fully account for the correlation among the genes. Here we propose to tackle this important feature of a gene set to improve statistical power in gene set analyses. We propose to model the effects of an independent variable, e.g., exposure/biological status (yes/no), on multiple gene expression values in a gene set using a multivariate linear regression model, where the correlation among the genes is explicitly modeled using a working covariance matrix. We develop TEGS (Test for the Effect of a Gene Set), a variance component test for the gene set effects by assuming a common distribution for regression coefficients in multivariate linear regression models, and calculate the p-values using permutation and a scaled chi-square approximation. We show using simulations that type I error is protected under different choices of working covariance matrices and power is improved as the working covariance approaches the true covariance. The global test is a special case of TEGS when correlation among genes in a gene set is ignored. Using both simulation data and a published diabetes dataset, we show that our test outperforms the commonly used approaches, the global test and gene set enrichment analysis (GSEA). We develop a gene set analyses method (TEGS) under the multivariate regression framework, which directly models the interdependence of the expression values in a gene set using a working covariance. TEGS outperforms two widely used methods, GSEA and global test in both simulation and a diabetes microarray data.

Generalized permutation entropy analysis based on the two-index entropic form S q , δ

NASA Astrophysics Data System (ADS)

Xu, Mengjia; Shang, Pengjian

2015-05-01

Permutation entropy (PE) is a novel measure to quantify the complexity of nonlinear time series. In this paper, we propose a generalized permutation entropy ( P E q , δ ) based on the recently postulated entropic form, S q , δ , which was proposed as an unification of the well-known Sq of nonextensive-statistical mechanics and S δ , a possibly appropriate candidate for the black-hole entropy. We find that P E q , δ with appropriate parameters can amplify minor changes and trends of complexities in comparison to PE. Experiments with this generalized permutation entropy method are performed with both synthetic and stock data showing its power. Results show that P E q , δ is an exponential function of q and the power ( k ( δ ) ) is a constant if δ is determined. Some discussions about k ( δ ) are provided. Besides, we also find some interesting results about power law.

A Flexible Computational Framework Using R and Map-Reduce for Permutation Tests of Massive Genetic Analysis of Complex Traits.

PubMed

Mahjani, Behrang; Toor, Salman; Nettelblad, Carl; Holmgren, Sverker

2017-01-01

In quantitative trait locus (QTL) mapping significance of putative QTL is often determined using permutation testing. The computational needs to calculate the significance level are immense, 10 4 up to 10 8 or even more permutations can be needed. We have previously introduced the PruneDIRECT algorithm for multiple QTL scan with epistatic interactions. This algorithm has specific strengths for permutation testing. Here, we present a flexible, parallel computing framework for identifying multiple interacting QTL using the PruneDIRECT algorithm which uses the map-reduce model as implemented in Hadoop. The framework is implemented in R, a widely used software tool among geneticists. This enables users to rearrange algorithmic steps to adapt genetic models, search algorithms, and parallelization steps to their needs in a flexible way. Our work underlines the maturity of accessing distributed parallel computing for computationally demanding bioinformatics applications through building workflows within existing scientific environments. We investigate the PruneDIRECT algorithm, comparing its performance to exhaustive search and DIRECT algorithm using our framework on a public cloud resource. We find that PruneDIRECT is vastly superior for permutation testing, and perform 2 ×10 5 permutations for a 2D QTL problem in 15 hours, using 100 cloud processes. We show that our framework scales out almost linearly for a 3D QTL search.

The coupling analysis between stock market indices based on permutation measures

NASA Astrophysics Data System (ADS)

Shi, Wenbin; Shang, Pengjian; Xia, Jianan; Yeh, Chien-Hung

2016-04-01

Many information-theoretic methods have been proposed for analyzing the coupling dependence between time series. And it is significant to quantify the correlation relationship between financial sequences since the financial market is a complex evolved dynamic system. Recently, we developed a new permutation-based entropy, called cross-permutation entropy (CPE), to detect the coupling structures between two synchronous time series. In this paper, we extend the CPE method to weighted cross-permutation entropy (WCPE), to address some of CPE's limitations, mainly its inability to differentiate between distinct patterns of a certain motif and the sensitivity of patterns close to the noise floor. It shows more stable and reliable results than CPE does when applied it to spiky data and AR(1) processes. Besides, we adapt the CPE method to infer the complexity of short-length time series by freely changing the time delay, and test it with Gaussian random series and random walks. The modified method shows the advantages in reducing deviations of entropy estimation compared with the conventional one. Finally, the weighted cross-permutation entropy of eight important stock indices from the world financial markets is investigated, and some useful and interesting empirical results are obtained.

Multivariate Phylogenetic Comparative Methods: Evaluations, Comparisons, and Recommendations.

PubMed

Adams, Dean C; Collyer, Michael L

2018-01-01

Recent years have seen increased interest in phylogenetic comparative analyses of multivariate data sets, but to date the varied proposed approaches have not been extensively examined. Here we review the mathematical properties required of any multivariate method, and specifically evaluate existing multivariate phylogenetic comparative methods in this context. Phylogenetic comparative methods based on the full multivariate likelihood are robust to levels of covariation among trait dimensions and are insensitive to the orientation of the data set, but display increasing model misspecification as the number of trait dimensions increases. This is because the expected evolutionary covariance matrix (V) used in the likelihood calculations becomes more ill-conditioned as trait dimensionality increases, and as evolutionary models become more complex. Thus, these approaches are only appropriate for data sets with few traits and many species. Methods that summarize patterns across trait dimensions treated separately (e.g., SURFACE) incorrectly assume independence among trait dimensions, resulting in nearly a 100% model misspecification rate. Methods using pairwise composite likelihood are highly sensitive to levels of trait covariation, the orientation of the data set, and the number of trait dimensions. The consequences of these debilitating deficiencies are that a user can arrive at differing statistical conclusions, and therefore biological inferences, simply from a dataspace rotation, like principal component analysis. By contrast, algebraic generalizations of the standard phylogenetic comparative toolkit that use the trace of covariance matrices are insensitive to levels of trait covariation, the number of trait dimensions, and the orientation of the data set. Further, when appropriate permutation tests are used, these approaches display acceptable Type I error and statistical power. We conclude that methods summarizing information across trait dimensions, as well as pairwise composite likelihood methods should be avoided, whereas algebraic generalizations of the phylogenetic comparative toolkit provide a useful means of assessing macroevolutionary patterns in multivariate data. Finally, we discuss areas in which multivariate phylogenetic comparative methods are still in need of future development; namely highly multivariate Ornstein-Uhlenbeck models and approaches for multivariate evolutionary model comparisons. © The Author(s) 2017. Published by Oxford University Press on behalf of the Systematic Biology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

MEMD-enhanced multivariate fuzzy entropy for the evaluation of complexity in biomedical signals.

PubMed

Azami, Hamed; Smith, Keith; Escudero, Javier

2016-08-01

Multivariate multiscale entropy (mvMSE) has been proposed as a combination of the coarse-graining process and multivariate sample entropy (mvSE) to quantify the irregularity of multivariate signals. However, both the coarse-graining process and mvSE may not be reliable for short signals. Although the coarse-graining process can be replaced with multivariate empirical mode decomposition (MEMD), the relative instability of mvSE for short signals remains a problem. Here, we address this issue by proposing the multivariate fuzzy entropy (mvFE) with a new fuzzy membership function. The results using white Gaussian noise show that the mvFE leads to more reliable and stable results, especially for short signals, in comparison with mvSE. Accordingly, we propose MEMD-enhanced mvFE to quantify the complexity of signals. The characteristics of brain regions influenced by partial epilepsy are investigated by focal and non-focal electroencephalogram (EEG) time series. In this sense, the proposed MEMD-enhanced mvFE and mvSE are employed to discriminate focal EEG signals from non-focal ones. The results demonstrate the MEMD-enhanced mvFE values have a smaller coefficient of variation in comparison with those obtained by the MEMD-enhanced mvSE, even for long signals. The results also show that the MEMD-enhanced mvFE has better performance to quantify focal and non-focal signals compared with multivariate multiscale permutation entropy.

Support vector machine learning-based fMRI data group analysis.

PubMed

Wang, Ze; Childress, Anna R; Wang, Jiongjiong; Detre, John A

2007-07-15

To explore the multivariate nature of fMRI data and to consider the inter-subject brain response discrepancies, a multivariate and brain response model-free method is fundamentally required. Two such methods are presented in this paper by integrating a machine learning algorithm, the support vector machine (SVM), and the random effect model. Without any brain response modeling, SVM was used to extract a whole brain spatial discriminance map (SDM), representing the brain response difference between the contrasted experimental conditions. Population inference was then obtained through the random effect analysis (RFX) or permutation testing (PMU) on the individual subjects' SDMs. Applied to arterial spin labeling (ASL) perfusion fMRI data, SDM RFX yielded lower false-positive rates in the null hypothesis test and higher detection sensitivity for synthetic activations with varying cluster size and activation strengths, compared to the univariate general linear model (GLM)-based RFX. For a sensory-motor ASL fMRI study, both SDM RFX and SDM PMU yielded similar activation patterns to GLM RFX and GLM PMU, respectively, but with higher t values and cluster extensions at the same significance level. Capitalizing on the absence of temporal noise correlation in ASL data, this study also incorporated PMU in the individual-level GLM and SVM analyses accompanied by group-level analysis through RFX or group-level PMU. Providing inferences on the probability of being activated or deactivated at each voxel, these individual-level PMU-based group analysis methods can be used to threshold the analysis results of GLM RFX, SDM RFX or SDM PMU.

An empirical study using permutation-based resampling in meta-regression

PubMed Central

2012-01-01

Background In meta-regression, as the number of trials in the analyses decreases, the risk of false positives or false negatives increases. This is partly due to the assumption of normality that may not hold in small samples. Creation of a distribution from the observed trials using permutation methods to calculate P values may allow for less spurious findings. Permutation has not been empirically tested in meta-regression. The objective of this study was to perform an empirical investigation to explore the differences in results for meta-analyses on a small number of trials using standard large sample approaches verses permutation-based methods for meta-regression. Methods We isolated a sample of randomized controlled clinical trials (RCTs) for interventions that have a small number of trials (herbal medicine trials). Trials were then grouped by herbal species and condition and assessed for methodological quality using the Jadad scale, and data were extracted for each outcome. Finally, we performed meta-analyses on the primary outcome of each group of trials and meta-regression for methodological quality subgroups within each meta-analysis. We used large sample methods and permutation methods in our meta-regression modeling. We then compared final models and final P values between methods. Results We collected 110 trials across 5 intervention/outcome pairings and 5 to 10 trials per covariate. When applying large sample methods and permutation-based methods in our backwards stepwise regression the covariates in the final models were identical in all cases. The P values for the covariates in the final model were larger in 78% (7/9) of the cases for permutation and identical for 22% (2/9) of the cases. Conclusions We present empirical evidence that permutation-based resampling may not change final models when using backwards stepwise regression, but may increase P values in meta-regression of multiple covariates for relatively small amount of trials. PMID:22587815

A Computationally Efficient Hypothesis Testing Method for Epistasis Analysis using Multifactor Dimensionality Reduction

PubMed Central

Pattin, Kristine A.; White, Bill C.; Barney, Nate; Gui, Jiang; Nelson, Heather H.; Kelsey, Karl R.; Andrew, Angeline S.; Karagas, Margaret R.; Moore, Jason H.

2008-01-01

Multifactor dimensionality reduction (MDR) was developed as a nonparametric and model-free data mining method for detecting, characterizing, and interpreting epistasis in the absence of significant main effects in genetic and epidemiologic studies of complex traits such as disease susceptibility. The goal of MDR is to change the representation of the data using a constructive induction algorithm to make nonadditive interactions easier to detect using any classification method such as naïve Bayes or logistic regression. Traditionally, MDR constructed variables have been evaluated with a naïve Bayes classifier that is combined with 10-fold cross validation to obtain an estimate of predictive accuracy or generalizability of epistasis models. Traditionally, we have used permutation testing to statistically evaluate the significance of models obtained through MDR. The advantage of permutation testing is that it controls for false-positives due to multiple testing. The disadvantage is that permutation testing is computationally expensive. This is in an important issue that arises in the context of detecting epistasis on a genome-wide scale. The goal of the present study was to develop and evaluate several alternatives to large-scale permutation testing for assessing the statistical significance of MDR models. Using data simulated from 70 different epistasis models, we compared the power and type I error rate of MDR using a 1000-fold permutation test with hypothesis testing using an extreme value distribution (EVD). We find that this new hypothesis testing method provides a reasonable alternative to the computationally expensive 1000-fold permutation test and is 50 times faster. We then demonstrate this new method by applying it to a genetic epidemiology study of bladder cancer susceptibility that was previously analyzed using MDR and assessed using a 1000-fold permutation test. PMID:18671250

Blocks in cycles and k-commuting permutations.

PubMed

Moreno, Rutilo; Rivera, Luis Manuel

2016-01-01

We introduce and study k -commuting permutations. One of our main results is a characterization of permutations that k -commute with a given permutation. Using this characterization, we obtain formulas for the number of permutations that k -commute with a permutation [Formula: see text], for some cycle types of [Formula: see text]. Our enumerative results are related with integer sequences in "The On-line Encyclopedia of Integer Sequences", and in some cases provide new interpretations for such sequences.

Fast algorithms for transforming back and forth between a signed permutation and its equivalent simple permutation.

PubMed

Gog, Simon; Bader, Martin

2008-10-01

The problem of sorting signed permutations by reversals is a well-studied problem in computational biology. The first polynomial time algorithm was presented by Hannenhalli and Pevzner in 1995. The algorithm was improved several times, and nowadays the most efficient algorithm has a subquadratic running time. Simple permutations played an important role in the development of these algorithms. Although the latest result of Tannier et al. does not require simple permutations, the preliminary version of their algorithm as well as the first polynomial time algorithm of Hannenhalli and Pevzner use the structure of simple permutations. More precisely, the latter algorithms require a precomputation that transforms a permutation into an equivalent simple permutation. To the best of our knowledge, all published algorithms for this transformation have at least a quadratic running time. For further investigations on genome rearrangement problems, the existence of a fast algorithm for the transformation could be crucial. Another important task is the back transformation, i.e. if we have a sorting on the simple permutation, transform it into a sorting on the original permutation. Again, the naive approach results in an algorithm with quadratic running time. In this paper, we present a linear time algorithm for transforming a permutation into an equivalent simple permutation, and an O(n log n) algorithm for the back transformation of the sorting sequence.

A Random Variable Related to the Inversion Vector of a Partial Random Permutation

ERIC Educational Resources Information Center

Laghate, Kavita; Deshpande, M. N.

2005-01-01

In this article, we define the inversion vector of a permutation of the integers 1, 2,..., n. We set up a particular kind of permutation, called a partial random permutation. The sum of the elements of the inversion vector of such a permutation is a random variable of interest.

A transposase strategy for creating libraries of circularly permuted proteins.

PubMed

Mehta, Manan M; Liu, Shirley; Silberg, Jonathan J

2012-05-01

A simple approach for creating libraries of circularly permuted proteins is described that is called PERMutation Using Transposase Engineering (PERMUTE). In PERMUTE, the transposase MuA is used to randomly insert a minitransposon that can function as a protein expression vector into a plasmid that contains the open reading frame (ORF) being permuted. A library of vectors that express different permuted variants of the ORF-encoded protein is created by: (i) using bacteria to select for target vectors that acquire an integrated minitransposon; (ii) excising the ensemble of ORFs that contain an integrated minitransposon from the selected vectors; and (iii) circularizing the ensemble of ORFs containing integrated minitransposons using intramolecular ligation. Construction of a Thermotoga neapolitana adenylate kinase (AK) library using PERMUTE revealed that this approach produces vectors that express circularly permuted proteins with distinct sequence diversity from existing methods. In addition, selection of this library for variants that complement the growth of Escherichia coli with a temperature-sensitive AK identified functional proteins with novel architectures, suggesting that PERMUTE will be useful for the directed evolution of proteins with new functions.

A transposase strategy for creating libraries of circularly permuted proteins

PubMed Central

Mehta, Manan M.; Liu, Shirley; Silberg, Jonathan J.

2012-01-01

A simple approach for creating libraries of circularly permuted proteins is described that is called PERMutation Using Transposase Engineering (PERMUTE). In PERMUTE, the transposase MuA is used to randomly insert a minitransposon that can function as a protein expression vector into a plasmid that contains the open reading frame (ORF) being permuted. A library of vectors that express different permuted variants of the ORF-encoded protein is created by: (i) using bacteria to select for target vectors that acquire an integrated minitransposon; (ii) excising the ensemble of ORFs that contain an integrated minitransposon from the selected vectors; and (iii) circularizing the ensemble of ORFs containing integrated minitransposons using intramolecular ligation. Construction of a Thermotoga neapolitana adenylate kinase (AK) library using PERMUTE revealed that this approach produces vectors that express circularly permuted proteins with distinct sequence diversity from existing methods. In addition, selection of this library for variants that complement the growth of Escherichia coli with a temperature-sensitive AK identified functional proteins with novel architectures, suggesting that PERMUTE will be useful for the directed evolution of proteins with new functions. PMID:22319214

[Local fractal analysis of noise-like time series by all permutations method for 1-115 min periods].

PubMed

Panchelyuga, V A; Panchelyuga, M S

2015-01-01

Results of local fractal analysis of 329-per-day time series of 239Pu alpha-decay rate fluctuations by means of all permutations method (APM) are presented. The APM-analysis reveals in the time series some steady frequency set. The coincidence of the frequency set with the Earth natural oscillations was demonstrated. A short review of works by different authors who analyzed the time series of fluctuations in processes of different nature is given. We have shown that the periods observed in those works correspond to the periods revealed in our study. It points to a common mechanism of the phenomenon observed.

Quantum image encryption based on restricted geometric and color transformations

NASA Astrophysics Data System (ADS)

Song, Xian-Hua; Wang, Shen; Abd El-Latif, Ahmed A.; Niu, Xia-Mu

2014-08-01

A novel encryption scheme for quantum images based on restricted geometric and color transformations is proposed. The new strategy comprises efficient permutation and diffusion properties for quantum image encryption. The core idea of the permutation stage is to scramble the codes of the pixel positions through restricted geometric transformations. Then, a new quantum diffusion operation is implemented on the permutated quantum image based on restricted color transformations. The encryption keys of the two stages are generated by two sensitive chaotic maps, which can ensure the security of the scheme. The final step, measurement, is built by the probabilistic model. Experiments conducted on statistical analysis demonstrate that significant improvements in the results are in favor of the proposed approach.

Hemodynamic Response to Interictal Epileptiform Discharges Addressed by Personalized EEG-fNIRS Recordings

PubMed Central

Pellegrino, Giovanni; Machado, Alexis; von Ellenrieder, Nicolas; Watanabe, Satsuki; Hall, Jeffery A.; Lina, Jean-Marc; Kobayashi, Eliane; Grova, Christophe

2016-01-01

Objective: We aimed at studying the hemodynamic response (HR) to Interictal Epileptic Discharges (IEDs) using patient-specific and prolonged simultaneous ElectroEncephaloGraphy (EEG) and functional Near InfraRed Spectroscopy (fNIRS) recordings. Methods: The epileptic generator was localized using Magnetoencephalography source imaging. fNIRS montage was tailored for each patient, using an algorithm to optimize the sensitivity to the epileptic generator. Optodes were glued using collodion to achieve prolonged acquisition with high quality signal. fNIRS data analysis was handled with no a priori constraint on HR time course, averaging fNIRS signals to similar IEDs. Cluster-permutation analysis was performed on 3D reconstructed fNIRS data to identify significant spatio-temporal HR clusters. Standard (GLM with fixed HRF) and cluster-permutation EEG-fMRI analyses were performed for comparison purposes. Results: fNIRS detected HR to IEDs for 8/9 patients. It mainly consisted oxy-hemoglobin increases (seven patients), followed by oxy-hemoglobin decreases (six patients). HR was lateralized in six patients and lasted from 8.5 to 30 s. Standard EEG-fMRI analysis detected an HR in 4/9 patients (4/9 without enough IEDs, 1/9 unreliable result). The cluster-permutation EEG-fMRI analysis restricted to the region investigated by fNIRS showed additional strong and non-canonical BOLD responses starting earlier than the IEDs and lasting up to 30 s. Conclusions: (i) EEG-fNIRS is suitable to detect the HR to IEDs and can outperform EEG-fMRI because of prolonged recordings and greater chance to detect IEDs; (ii) cluster-permutation analysis unveils additional HR features underestimated when imposing a canonical HR function (iii) the HR is often bilateral and lasts up to 30 s. PMID:27047325

Multivariate statistical analysis of diffusion imaging parameters using partial least squares: Application to white matter variations in Alzheimer's disease.

PubMed

Konukoglu, Ender; Coutu, Jean-Philippe; Salat, David H; Fischl, Bruce

2016-07-01

Diffusion magnetic resonance imaging (dMRI) is a unique technology that allows the noninvasive quantification of microstructural tissue properties of the human brain in healthy subjects as well as the probing of disease-induced variations. Population studies of dMRI data have been essential in identifying pathological structural changes in various conditions, such as Alzheimer's and Huntington's diseases (Salat et al., 2010; Rosas et al., 2006). The most common form of dMRI involves fitting a tensor to the underlying imaging data (known as diffusion tensor imaging, or DTI), then deriving parametric maps, each quantifying a different aspect of the underlying microstructure, e.g. fractional anisotropy and mean diffusivity. To date, the statistical methods utilized in most DTI population studies either analyzed only one such map or analyzed several of them, each in isolation. However, it is most likely that variations in the microstructure due to pathology or normal variability would affect several parameters simultaneously, with differing variations modulating the various parameters to differing degrees. Therefore, joint analysis of the available diffusion maps can be more powerful in characterizing histopathology and distinguishing between conditions than the widely used univariate analysis. In this article, we propose a multivariate approach for statistical analysis of diffusion parameters that uses partial least squares correlation (PLSC) analysis and permutation testing as building blocks in a voxel-wise fashion. Stemming from the common formulation, we present three different multivariate procedures for group analysis, regressing-out nuisance parameters and comparing effects of different conditions. We used the proposed procedures to study the effects of non-demented aging, Alzheimer's disease and mild cognitive impairment on the white matter. Here, we present results demonstrating that the proposed PLSC-based approach can differentiate between effects of different conditions in the same region as well as uncover spatial variations of effects across the white matter. The proposed procedures were able to answer questions on structural variations such as: "are there regions in the white matter where Alzheimer's disease has a different effect than aging or similar effect as aging?" and "are there regions in the white matter that are affected by both mild cognitive impairment and Alzheimer's disease but with differing multivariate effects?" Copyright © 2016 Elsevier Inc. All rights reserved.

Multivariate Statistical Analysis of Diffusion Imaging Parameters using Partial Least Squares: Application to White Matter Variations in Alzheimer’s Disease

PubMed Central

Konukoglu, Ender; Coutu, Jean-Philippe; Salat, David H.; Fischl, Bruce

2016-01-01

Diffusion magnetic resonance imaging (dMRI) is a unique technology that allows the noninvasive quantification of microstructural tissue properties of the human brain in healthy subjects as well as the probing of disease-induced variations. Population studies of dMRI data have been essential in identifying pathological structural changes in various conditions, such as Alzheimer’s and Huntington’s diseases1,2. The most common form of dMRI involves fitting a tensor to the underlying imaging data (known as Diffusion Tensor Imaging, or DTI), then deriving parametric maps, each quantifying a different aspect of the underlying microstructure, e.g. fractional anisotropy and mean diffusivity. To date, the statistical methods utilized in most DTI population studies either analyzed only one such map or analyzed several of them, each in isolation. However, it is most likely that variations in the microstructure due to pathology or normal variability would affect several parameters simultaneously, with differing variations modulating the various parameters to differing degrees. Therefore, joint analysis of the available diffusion maps can be more powerful in characterizing histopathology and distinguishing between conditions than the widely used univariate analysis. In this article, we propose a multivariate approach for statistical analysis of diffusion parameters that uses partial least squares correlation (PLSC) analysis and permutation testing as building blocks in a voxel-wise fashion. Stemming from the common formulation, we present three different multivariate procedures for group analysis, regressing-out nuisance parameters and comparing effects of different conditions. We used the proposed procedures to study the effects of non-demented aging, Alzheimer’s disease and mild cognitive impairment on the white matter. Here, we present results demonstrating that the proposed PLSC-based approach can differentiate between effects of different conditions in the same region as well as uncover spatial variations of effects across the white matter. The proposed procedures were able to answer questions on structural variations such as: “are there regions in the white matter where Alzheimer’s disease has a different effect than aging or similar effect as aging?” and “are there regions in the white matter that are affected by both mild cognitive impairment and Alzheimer’s disease but with differing multivariate effects?” PMID:27103138

Diagnostic index of 3D osteoarthritic changes in TMJ condylar morphology

NASA Astrophysics Data System (ADS)

Gomes, Liliane R.; Gomes, Marcelo; Jung, Bryan; Paniagua, Beatriz; Ruellas, Antonio C.; Gonçalves, João. Roberto; Styner, Martin A.; Wolford, Larry; Cevidanes, Lucia

2015-03-01

The aim of this study was to investigate imaging statistical approaches for classifying 3D osteoarthritic morphological variations among 169 Temporomandibular Joint (TMJ) condyles. Cone beam Computed Tomography (CBCT) scans were acquired from 69 patients with long-term TMJ Osteoarthritis (OA) (39.1 ± 15.7 years), 15 patients at initial diagnosis of OA (44.9 ± 14.8 years) and 7 healthy controls (43 ± 12.4 years). 3D surface models of the condyles were constructed and Shape Correspondence was used to establish correspondent points on each model. The statistical framework included a multivariate analysis of covariance (MANCOVA) and Direction-Projection- Permutation (DiProPerm) for testing statistical significance of the differences between healthy control and the OA group determined by clinical and radiographic diagnoses. Unsupervised classification using hierarchical agglomerative clustering (HAC) was then conducted. Condylar morphology in OA and healthy subjects varied widely. Compared with healthy controls, OA average condyle was statistically significantly smaller in all dimensions except its anterior surface. Significant flattening of the lateral pole was noticed at initial diagnosis (p < 0.05). It was observed areas of 3.88 mm bone resorption at the superior surface and 3.10 mm bone apposition at the anterior aspect of the long-term OA average model. 1000 permutation statistics of DiProPerm supported a significant difference between the healthy control group and OA group (t = 6.7, empirical p-value = 0.001). Clinically meaningful unsupervised classification of TMJ condylar morphology determined a preliminary diagnostic index of 3D osteoarthritic changes, which may be the first step towards a more targeted diagnosis of this condition.

Encoding Sequential Information in Semantic Space Models: Comparing Holographic Reduced Representation and Random Permutation

PubMed Central

Recchia, Gabriel; Sahlgren, Magnus; Kanerva, Pentti; Jones, Michael N.

2015-01-01

Circular convolution and random permutation have each been proposed as neurally plausible binding operators capable of encoding sequential information in semantic memory. We perform several controlled comparisons of circular convolution and random permutation as means of encoding paired associates as well as encoding sequential information. Random permutations outperformed convolution with respect to the number of paired associates that can be reliably stored in a single memory trace. Performance was equal on semantic tasks when using a small corpus, but random permutations were ultimately capable of achieving superior performance due to their higher scalability to large corpora. Finally, “noisy” permutations in which units are mapped to other units arbitrarily (no one-to-one mapping) perform nearly as well as true permutations. These findings increase the neurological plausibility of random permutations and highlight their utility in vector space models of semantics. PMID:25954306

Sorting permutations by prefix and suffix rearrangements.

PubMed

Lintzmayer, Carla Negri; Fertin, Guillaume; Dias, Zanoni

2017-02-01

Some interesting combinatorial problems have been motivated by genome rearrangements, which are mutations that affect large portions of a genome. When we represent genomes as permutations, the goal is to transform a given permutation into the identity permutation with the minimum number of rearrangements. When they affect segments from the beginning (respectively end) of the permutation, they are called prefix (respectively suffix) rearrangements. This paper presents results for rearrangement problems that involve prefix and suffix versions of reversals and transpositions considering unsigned and signed permutations. We give 2-approximation and ([Formula: see text])-approximation algorithms for these problems, where [Formula: see text] is a constant divided by the number of breakpoints (pairs of consecutive elements that should not be consecutive in the identity permutation) in the input permutation. We also give bounds for the diameters concerning these problems and provide ways of improving the practical results of our algorithms.

A Reversible Logical Circuit Synthesis Algorithm Based on Decomposition of Cycle Representations of Permutations

NASA Astrophysics Data System (ADS)

Zhu, Wei; Li, Zhiqiang; Zhang, Gaoman; Pan, Suhan; Zhang, Wei

2018-05-01

A reversible function is isomorphic to a permutation and an arbitrary permutation can be represented by a series of cycles. A new synthesis algorithm for 3-qubit reversible circuits was presented. It consists of two parts, the first part used the Number of reversible function's Different Bits (NDBs) to decide whether the NOT gate should be added to decrease the Hamming distance of the input and output vectors; the second part was based on the idea of exploring properties of the cycle representation of permutations, decomposed the cycles to make the permutation closer to the identity permutation and finally turn into the identity permutation, it was realized by using totally controlled Toffoli gates with positive and negative controls.

permGPU: Using graphics processing units in RNA microarray association studies.

PubMed

Shterev, Ivo D; Jung, Sin-Ho; George, Stephen L; Owzar, Kouros

2010-06-16

Many analyses of microarray association studies involve permutation, bootstrap resampling and cross-validation, that are ideally formulated as embarrassingly parallel computing problems. Given that these analyses are computationally intensive, scalable approaches that can take advantage of multi-core processor systems need to be developed. We have developed a CUDA based implementation, permGPU, that employs graphics processing units in microarray association studies. We illustrate the performance and applicability of permGPU within the context of permutation resampling for a number of test statistics. An extensive simulation study demonstrates a dramatic increase in performance when using permGPU on an NVIDIA GTX 280 card compared to an optimized C/C++ solution running on a conventional Linux server. permGPU is available as an open-source stand-alone application and as an extension package for the R statistical environment. It provides a dramatic increase in performance for permutation resampling analysis in the context of microarray association studies. The current version offers six test statistics for carrying out permutation resampling analyses for binary, quantitative and censored time-to-event traits.

Controllability of symmetric spin networks

NASA Astrophysics Data System (ADS)

Albertini, Francesca; D'Alessandro, Domenico

2018-05-01

We consider a network of n spin 1/2 systems which are pairwise interacting via Ising interaction and are controlled by the same electro-magnetic control field. Such a system presents symmetries since the Hamiltonian is unchanged if we permute two spins. This prevents full (operator) controllability, in that not every unitary evolution can be obtained. We prove however that controllability is verified if we restrict ourselves to unitary evolutions which preserve the above permutation invariance. For low dimensional cases, n = 2 and n = 3, we provide an analysis of the Lie group of available evolutions and give explicit control laws to transfer between two arbitrary permutation invariant states. This class of states includes highly entangled states such as Greenberger-Horne-Zeilinger (GHZ) states and W states, which are of interest in quantum information.

A permutation information theory tour through different interest rate maturities: the Libor case.

PubMed

Bariviera, Aurelio Fernández; Guercio, María Belén; Martinez, Lisana B; Rosso, Osvaldo A

2015-12-13

This paper analyses Libor interest rates for seven different maturities and referred to operations in British pounds, euros, Swiss francs and Japanese yen, during the period 2001-2015. The analysis is performed by means of two quantifiers derived from information theory: the permutation Shannon entropy and the permutation Fisher information measure. An anomalous behaviour in the Libor is detected in all currencies except euros during the years 2006-2012. The stochastic switch is more severe in one, two and three months maturities. Given the special mechanism of Libor setting, we conjecture that the behaviour could have been produced by the manipulation that was uncovered by financial authorities. We argue that our methodology is pertinent as a market overseeing instrument. © 2015 The Author(s).

In situ effects of titanium dioxide nanoparticles on community structure of freshwater benthic macroinvertebrates.

PubMed

Jovanović, Boris; Milošević, Djuradj; Piperac, Milica Stojković; Savić, Ana

2016-06-01

For the first time in the current literature, the effect of titanium dioxide (TiO2) nanoparticles on the community structure of macroinvertebrates has been investigated in situ. Macroinvertebrates were exposed for 100 days to an environmentally relevant concentration of TiO2 nanoparticles, 25 mg kg(-1) in sediment. Czekanowski's index was 0.61, meaning 39% of the macroinvertebrate community structure was affected by the TiO2 treatment. Non-metric multidimensional scaling (NMDS) visualized the qualitative and quantitative variability of macroinvertebrates at the community level among all samples. A distance-based permutational multivariate analysis of variance (PERMANOVA) revealed the significant effect of TiO2 on the macroinvertebrate community structure. The indicator value analysis showed that the relative frequency and abundance of Planorbarius corneus and Radix labiata were significantly lower in the TiO2 treatment than in the control. Meanwhile, Ceratopogonidae, showed a significantly higher relative frequency and abundance in the TiO2 treatment than in the control. Copyright © 2016 Elsevier Ltd. All rights reserved.

Inferring the Presence of Reverse Proxies Through Timing Analysis

DTIC Science & Technology

2015-06-01

16 Figure 3.2 The three different instances of timing measurement configurations 17 Figure 3.3 Permutation of a web request iteration...Their data showed that they could detect at least 6 bits of entropy between unlike devices and that it was enough to determine that they are in fact...depending on the permutation being executed so that every iteration was conducted under the same distance 15 City   Lat   Long   City   Lat   Long

Permutation entropy and statistical complexity analysis of turbulence in laboratory plasmas and the solar wind.

PubMed

Weck, P J; Schaffner, D A; Brown, M R; Wicks, R T

2015-02-01

The Bandt-Pompe permutation entropy and the Jensen-Shannon statistical complexity are used to analyze fluctuating time series of three different turbulent plasmas: the magnetohydrodynamic (MHD) turbulence in the plasma wind tunnel of the Swarthmore Spheromak Experiment (SSX), drift-wave turbulence of ion saturation current fluctuations in the edge of the Large Plasma Device (LAPD), and fully developed turbulent magnetic fluctuations of the solar wind taken from the Wind spacecraft. The entropy and complexity values are presented as coordinates on the CH plane for comparison among the different plasma environments and other fluctuation models. The solar wind is found to have the highest permutation entropy and lowest statistical complexity of the three data sets analyzed. Both laboratory data sets have larger values of statistical complexity, suggesting that these systems have fewer degrees of freedom in their fluctuations, with SSX magnetic fluctuations having slightly less complexity than the LAPD edge I(sat). The CH plane coordinates are compared to the shape and distribution of a spectral decomposition of the wave forms. These results suggest that fully developed turbulence (solar wind) occupies the lower-right region of the CH plane, and that other plasma systems considered to be turbulent have less permutation entropy and more statistical complexity. This paper presents use of this statistical analysis tool on solar wind plasma, as well as on an MHD turbulent experimental plasma.

Effects of an artificial oyster shell reef on macrobenthic communities in Rongcheng Bay, East China

NASA Astrophysics Data System (ADS)

Xu, Qinzeng; Zhang, Libin; Zhang, Tao; Zhou, Yi; Xia, Sudong; Liu, Hui; Yang, Hongsheng

2014-01-01

An artificial oyster shell reef was deployed in Rongcheng Bay, East China. However, the effects of this reef on the surrounding macrobenthic communities were unknown. We compared sedimentary factors, macrobenthic biomass, abundance, and community composition and ecological indicators between the reef and non-reef areas over a one year period. The mean values for chlorophyll a (Chl a), total organic matter (TOM), total organic carbon (TOC), and total nitrogen (TN) content in surface sediments in the reef area were slightly higher than those in the non-reef area. The Chl a levels differed significantly between the two areas, but the TOM, TOC, and TN were not significantly different. The abundance of crustaceans was significantly different between the two areas, but the abundance and biomass of polychaetes, echinoderms, mollusk did not differ significantly. The permutational multivariate analysis of variance (PERMANOVA) revealed that the macrobenthic community differed significantly through time and analysis of similarity multivariate analyses (ANOSIM) revealed that the macrobenthic community differed significantly in some months. The ecological indicators revealed that the environmental quality of the reef area was slightly better than that of the non-reef area. Overall, our results suggest that the artificial oyster shell reef may change the macrobenthic community and the quality of the environment. Despite the lack of an effect in the short term, long-term monitoring is still needed to evaluate the effects of artificial oyster shell reefs on macrobenthic communities.

Effective Iterated Greedy Algorithm for Flow-Shop Scheduling Problems with Time lags

NASA Astrophysics Data System (ADS)

ZHAO, Ning; YE, Song; LI, Kaidian; CHEN, Siyu

2017-05-01

Flow shop scheduling problem with time lags is a practical scheduling problem and attracts many studies. Permutation problem(PFSP with time lags) is concentrated but non-permutation problem(non-PFSP with time lags) seems to be neglected. With the aim to minimize the makespan and satisfy time lag constraints, efficient algorithms corresponding to PFSP and non-PFSP problems are proposed, which consist of iterated greedy algorithm for permutation(IGTLP) and iterated greedy algorithm for non-permutation (IGTLNP). The proposed algorithms are verified using well-known simple and complex instances of permutation and non-permutation problems with various time lag ranges. The permutation results indicate that the proposed IGTLP can reach near optimal solution within nearly 11% computational time of traditional GA approach. The non-permutation results indicate that the proposed IG can reach nearly same solution within less than 1% computational time compared with traditional GA approach. The proposed research combines PFSP and non-PFSP together with minimal and maximal time lag consideration, which provides an interesting viewpoint for industrial implementation.

Decryption of pure-position permutation algorithms.

PubMed

Zhao, Xiao-Yu; Chen, Gang; Zhang, Dan; Wang, Xiao-Hong; Dong, Guang-Chang

2004-07-01

Pure position permutation image encryption algorithms, commonly used as image encryption investigated in this work are unfortunately frail under known-text attack. In view of the weakness of pure position permutation algorithm, we put forward an effective decryption algorithm for all pure-position permutation algorithms. First, a summary of the pure position permutation image encryption algorithms is given by introducing the concept of ergodic matrices. Then, by using probability theory and algebraic principles, the decryption probability of pure-position permutation algorithms is verified theoretically; and then, by defining the operation system of fuzzy ergodic matrices, we improve a specific decryption algorithm. Finally, some simulation results are shown.

Weight distributions for turbo codes using random and nonrandom permutations

NASA Technical Reports Server (NTRS)

Dolinar, S.; Divsalar, D.

1995-01-01

This article takes a preliminary look at the weight distributions achievable for turbo codes using random, nonrandom, and semirandom permutations. Due to the recursiveness of the encoders, it is important to distinguish between self-terminating and non-self-terminating input sequences. The non-self-terminating sequences have little effect on decoder performance, because they accumulate high encoded weight until they are artificially terminated at the end of the block. From probabilistic arguments based on selecting the permutations randomly, it is concluded that the self-terminating weight-2 data sequences are the most important consideration in the design of constituent codes; higher-weight self-terminating sequences have successively decreasing importance. Also, increasing the number of codes and, correspondingly, the number of permutations makes it more and more likely that the bad input sequences will be broken up by one or more of the permuters. It is possible to design nonrandom permutations that ensure that the minimum distance due to weight-2 input sequences grows roughly as the square root of (2N), where N is the block length. However, these nonrandom permutations amplify the bad effects of higher-weight inputs, and as a result they are inferior in performance to randomly selected permutations. But there are 'semirandom' permutations that perform nearly as well as the designed nonrandom permutations with respect to weight-2 input sequences and are not as susceptible to being foiled by higher-weight inputs.

PERMutation Using Transposase Engineering (PERMUTE): A Simple Approach for Constructing Circularly Permuted Protein Libraries.

PubMed

Jones, Alicia M; Atkinson, Joshua T; Silberg, Jonathan J

2017-01-01

Rearrangements that alter the order of a protein's sequence are used in the lab to study protein folding, improve activity, and build molecular switches. One of the simplest ways to rearrange a protein sequence is through random circular permutation, where native protein termini are linked together and new termini are created elsewhere through random backbone fission. Transposase mutagenesis has emerged as a simple way to generate libraries encoding different circularly permuted variants of proteins. With this approach, a synthetic transposon (called a permuteposon) is randomly inserted throughout a circularized gene to generate vectors that express different permuted variants of a protein. In this chapter, we outline the protocol for constructing combinatorial libraries of circularly permuted proteins using transposase mutagenesis, and we describe the different permuteposons that have been developed to facilitate library construction.

Identifying Neural Patterns of Functional Dyspepsia Using Multivariate Pattern Analysis: A Resting-State fMRI Study

PubMed Central

Liu, Peng; Qin, Wei; Wang, Jingjing; Zeng, Fang; Zhou, Guangyu; Wen, Haixia; von Deneen, Karen M.; Liang, Fanrong; Gong, Qiyong; Tian, Jie

2013-01-01

Background Previous imaging studies on functional dyspepsia (FD) have focused on abnormal brain functions during special tasks, while few studies concentrated on the resting-state abnormalities of FD patients, which might be potentially valuable to provide us with direct information about the neural basis of FD. The main purpose of the current study was thereby to characterize the distinct patterns of resting-state function between FD patients and healthy controls (HCs). Methodology/Principal Findings Thirty FD patients and thirty HCs were enrolled and experienced 5-mintue resting-state scanning. Based on the support vector machine (SVM), we applied multivariate pattern analysis (MVPA) to investigate the differences of resting-state function mapped by regional homogeneity (ReHo). A classifier was designed by using the principal component analysis and the linear SVM. Permutation test was then employed to identify the significant contribution to the final discrimination. The results displayed that the mean classifier accuracy was 86.67%, and highly discriminative brain regions mainly included the prefrontal cortex (PFC), orbitofrontal cortex (OFC), supplementary motor area (SMA), temporal pole (TP), insula, anterior/middle cingulate cortex (ACC/MCC), thalamus, hippocampus (HIPP)/parahippocamus (ParaHIPP) and cerebellum. Correlation analysis revealed significant correlations between ReHo values in certain regions of interest (ROI) and the FD symptom severity and/or duration, including the positive correlations between the dmPFC, pACC and the symptom severity; whereas, the positive correlations between the MCC, OFC, insula, TP and FD duration. Conclusions These findings indicated that significantly distinct patterns existed between FD patients and HCs during the resting-state, which could expand our understanding of the neural basis of FD. Meanwhile, our results possibly showed potential feasibility of functional magnetic resonance imaging diagnostic assay for FD. PMID:23874543

Chaotic Image Encryption Algorithm Based on Bit Permutation and Dynamic DNA Encoding.

PubMed

Zhang, Xuncai; Han, Feng; Niu, Ying

2017-01-01

With the help of the fact that chaos is sensitive to initial conditions and pseudorandomness, combined with the spatial configurations in the DNA molecule's inherent and unique information processing ability, a novel image encryption algorithm based on bit permutation and dynamic DNA encoding is proposed here. The algorithm first uses Keccak to calculate the hash value for a given DNA sequence as the initial value of a chaotic map; second, it uses a chaotic sequence to scramble the image pixel locations, and the butterfly network is used to implement the bit permutation. Then, the image is coded into a DNA matrix dynamic, and an algebraic operation is performed with the DNA sequence to realize the substitution of the pixels, which further improves the security of the encryption. Finally, the confusion and diffusion properties of the algorithm are further enhanced by the operation of the DNA sequence and the ciphertext feedback. The results of the experiment and security analysis show that the algorithm not only has a large key space and strong sensitivity to the key but can also effectively resist attack operations such as statistical analysis and exhaustive analysis.

Chaotic Image Encryption Algorithm Based on Bit Permutation and Dynamic DNA Encoding

PubMed Central

2017-01-01

With the help of the fact that chaos is sensitive to initial conditions and pseudorandomness, combined with the spatial configurations in the DNA molecule's inherent and unique information processing ability, a novel image encryption algorithm based on bit permutation and dynamic DNA encoding is proposed here. The algorithm first uses Keccak to calculate the hash value for a given DNA sequence as the initial value of a chaotic map; second, it uses a chaotic sequence to scramble the image pixel locations, and the butterfly network is used to implement the bit permutation. Then, the image is coded into a DNA matrix dynamic, and an algebraic operation is performed with the DNA sequence to realize the substitution of the pixels, which further improves the security of the encryption. Finally, the confusion and diffusion properties of the algorithm are further enhanced by the operation of the DNA sequence and the ciphertext feedback. The results of the experiment and security analysis show that the algorithm not only has a large key space and strong sensitivity to the key but can also effectively resist attack operations such as statistical analysis and exhaustive analysis. PMID:28912802

Weighted fractional permutation entropy and fractional sample entropy for nonlinear Potts financial dynamics

NASA Astrophysics Data System (ADS)

Xu, Kaixuan; Wang, Jun

2017-02-01

In this paper, recently introduced permutation entropy and sample entropy are further developed to the fractional cases, weighted fractional permutation entropy (WFPE) and fractional sample entropy (FSE). The fractional order generalization of information entropy is utilized in the above two complexity approaches, to detect the statistical characteristics of fractional order information in complex systems. The effectiveness analysis of proposed methods on the synthetic data and the real-world data reveals that tuning the fractional order allows a high sensitivity and more accurate characterization to the signal evolution, which is useful in describing the dynamics of complex systems. Moreover, the numerical research on nonlinear complexity behaviors is compared between the returns series of Potts financial model and the actual stock markets. And the empirical results confirm the feasibility of the proposed model.

Rapid and Accurate Multiple Testing Correction and Power Estimation for Millions of Correlated Markers

PubMed Central

Han, Buhm; Kang, Hyun Min; Eskin, Eleazar

2009-01-01

With the development of high-throughput sequencing and genotyping technologies, the number of markers collected in genetic association studies is growing rapidly, increasing the importance of methods for correcting for multiple hypothesis testing. The permutation test is widely considered the gold standard for accurate multiple testing correction, but it is often computationally impractical for these large datasets. Recently, several studies proposed efficient alternative approaches to the permutation test based on the multivariate normal distribution (MVN). However, they cannot accurately correct for multiple testing in genome-wide association studies for two reasons. First, these methods require partitioning of the genome into many disjoint blocks and ignore all correlations between markers from different blocks. Second, the true null distribution of the test statistic often fails to follow the asymptotic distribution at the tails of the distribution. We propose an accurate and efficient method for multiple testing correction in genome-wide association studies—SLIDE. Our method accounts for all correlation within a sliding window and corrects for the departure of the true null distribution of the statistic from the asymptotic distribution. In simulations using the Wellcome Trust Case Control Consortium data, the error rate of SLIDE's corrected p-values is more than 20 times smaller than the error rate of the previous MVN-based methods' corrected p-values, while SLIDE is orders of magnitude faster than the permutation test and other competing methods. We also extend the MVN framework to the problem of estimating the statistical power of an association study with correlated markers and propose an efficient and accurate power estimation method SLIP. SLIP and SLIDE are available at http://slide.cs.ucla.edu. PMID:19381255

Opposition-Based Memetic Algorithm and Hybrid Approach for Sorting Permutations by Reversals.

PubMed

Soncco-Álvarez, José Luis; Muñoz, Daniel M; Ayala-Rincón, Mauricio

2018-02-21

Sorting unsigned permutations by reversals is a difficult problem; indeed, it was proved to be NP-hard by Caprara (1997). Because of its high complexity, many approximation algorithms to compute the minimal reversal distance were proposed until reaching the nowadays best-known theoretical ratio of 1.375. In this article, two memetic algorithms to compute the reversal distance are proposed. The first one uses the technique of opposition-based learning leading to an opposition-based memetic algorithm; the second one improves the previous algorithm by applying the heuristic of two breakpoint elimination leading to a hybrid approach. Several experiments were performed with one-hundred randomly generated permutations, single benchmark permutations, and biological permutations. Results of the experiments showed that the proposed OBMA and Hybrid-OBMA algorithms achieve the best results for practical cases, that is, for permutations of length up to 120. Also, Hybrid-OBMA showed to improve the results of OBMA for permutations greater than or equal to 60. The applicability of our proposed algorithms was checked processing permutations based on biological data, in which case OBMA gave the best average results for all instances.

Four applications of permutation methods to testing a single-mediator model.

PubMed

Taylor, Aaron B; MacKinnon, David P

2012-09-01

Four applications of permutation tests to the single-mediator model are described and evaluated in this study. Permutation tests work by rearranging data in many possible ways in order to estimate the sampling distribution for the test statistic. The four applications to mediation evaluated here are the permutation test of ab, the permutation joint significance test, and the noniterative and iterative permutation confidence intervals for ab. A Monte Carlo simulation study was used to compare these four tests with the four best available tests for mediation found in previous research: the joint significance test, the distribution of the product test, and the percentile and bias-corrected bootstrap tests. We compared the different methods on Type I error, power, and confidence interval coverage. The noniterative permutation confidence interval for ab was the best performer among the new methods. It successfully controlled Type I error, had power nearly as good as the most powerful existing methods, and had better coverage than any existing method. The iterative permutation confidence interval for ab had lower power than do some existing methods, but it performed better than any other method in terms of coverage. The permutation confidence interval methods are recommended when estimating a confidence interval is a primary concern. SPSS and SAS macros that estimate these confidence intervals are provided.

Circular Permutation of a Chaperonin Protein: Biophysics and Application to Nanotechnology

NASA Technical Reports Server (NTRS)

Paavola, Chad; Chan, Suzanne; Li, Yi-Fen; McMillan, R. Andrew; Trent, Jonathan

2004-01-01

We have designed five circular permutants of a chaperonin protein derived from the hyperthermophilic organism Sulfolobus shibatae. These permuted proteins were expressed in E. coli and are well-folded. Furthermore, all the permutants assemble into 18-mer double rings of the same form as the wild-type protein. We characterized the thermodynamics of folding for each permutant by both guanidine denaturation and differential scanning calorimetry. We also examined the assembly of chaperonin rings into higher order structures that may be used as nanoscale templates. The results show that circular permutation can be used to tune the thermodynamic properties of a protein template as well as facilitating the fusion of peptides, binding proteins or enzymes onto nanostructured templates.

The structure of a thermophilic kinase shapes fitness upon random circular permutation

PubMed Central

Jones, Alicia M.; Mehta, Manan M.; Thomas, Emily E.; Atkinson, Joshua T.; Segall-Shapiro, Thomas H.; Liu, Shirley; Silberg, Jonathan J.

2016-01-01

Proteins can be engineered for synthetic biology through circular permutation, a sequence rearrangement where native protein termini become linked and new termini are created elsewhere through backbone fission. However, it remains challenging to anticipate a protein’s functional tolerance to circular permutation. Here, we describe new transposons for creating libraries of randomly circularly permuted proteins that minimize peptide additions at their termini, and we use transposase mutagenesis to study the tolerance of a thermophilic adenylate kinase (AK) to circular permutation. We find that libraries expressing permuted AK with either short or long peptides amended to their N-terminus yield distinct sets of active variants and present evidence that this trend arises because permuted protein expression varies across libraries. Mapping all sites that tolerate backbone cleavage onto AK structure reveals that the largest contiguous regions of sequence that lack cleavage sites are proximal to the phosphotransfer site. A comparison of our results with a range of structure-derived parameters further showed that retention of function correlates to the strongest extent with the distance to the phosphotransfer site, amino acid variability in an AK family sequence alignment, and residue-level deviations in superimposed AK structures. Our work illustrates how permuted protein libraries can be created with minimal peptide additions using transposase mutagenesis, and they reveal a challenge of maintaining consistent expression across permuted variants in a library that minimizes peptide additions. Furthermore, these findings provide a basis for interpreting responses of thermophilic phosphotransferases to circular permutation by calibrating how different structure-derived parameters relate to retention of function in a cellular selection. PMID:26976658

The Structure of a Thermophilic Kinase Shapes Fitness upon Random Circular Permutation.

PubMed

Jones, Alicia M; Mehta, Manan M; Thomas, Emily E; Atkinson, Joshua T; Segall-Shapiro, Thomas H; Liu, Shirley; Silberg, Jonathan J

2016-05-20

Proteins can be engineered for synthetic biology through circular permutation, a sequence rearrangement in which native protein termini become linked and new termini are created elsewhere through backbone fission. However, it remains challenging to anticipate a protein's functional tolerance to circular permutation. Here, we describe new transposons for creating libraries of randomly circularly permuted proteins that minimize peptide additions at their termini, and we use transposase mutagenesis to study the tolerance of a thermophilic adenylate kinase (AK) to circular permutation. We find that libraries expressing permuted AKs with either short or long peptides amended to their N-terminus yield distinct sets of active variants and present evidence that this trend arises because permuted protein expression varies across libraries. Mapping all sites that tolerate backbone cleavage onto AK structure reveals that the largest contiguous regions of sequence that lack cleavage sites are proximal to the phosphotransfer site. A comparison of our results with a range of structure-derived parameters further showed that retention of function correlates to the strongest extent with the distance to the phosphotransfer site, amino acid variability in an AK family sequence alignment, and residue-level deviations in superimposed AK structures. Our work illustrates how permuted protein libraries can be created with minimal peptide additions using transposase mutagenesis, and it reveals a challenge of maintaining consistent expression across permuted variants in a library that minimizes peptide additions. Furthermore, these findings provide a basis for interpreting responses of thermophilic phosphotransferases to circular permutation by calibrating how different structure-derived parameters relate to retention of function in a cellular selection.

A Weak Quantum Blind Signature with Entanglement Permutation

NASA Astrophysics Data System (ADS)

Lou, Xiaoping; Chen, Zhigang; Guo, Ying

2015-09-01

Motivated by the permutation encryption algorithm, a weak quantum blind signature (QBS) scheme is proposed. It involves three participants, including the sender Alice, the signatory Bob and the trusted entity Charlie, in four phases, i.e., initializing phase, blinding phase, signing phase and verifying phase. In a small-scale quantum computation network, Alice blinds the message based on a quantum entanglement permutation encryption algorithm that embraces the chaotic position string. Bob signs the blinded message with private parameters shared beforehand while Charlie verifies the signature's validity and recovers the original message. Analysis shows that the proposed scheme achieves the secure blindness for the signer and traceability for the message owner with the aid of the authentic arbitrator who plays a crucial role when a dispute arises. In addition, the signature can neither be forged nor disavowed by the malicious attackers. It has a wide application to E-voting and E-payment system, etc.

Teaching Tip: When a Matrix and Its Inverse Are Stochastic

ERIC Educational Resources Information Center

Ding, J.; Rhee, N. H.

2013-01-01

A stochastic matrix is a square matrix with nonnegative entries and row sums 1. The simplest example is a permutation matrix, whose rows permute the rows of an identity matrix. A permutation matrix and its inverse are both stochastic. We prove the converse, that is, if a matrix and its inverse are both stochastic, then it is a permutation matrix.

Permutation-based inference for the AUC: A unified approach for continuous and discontinuous data.

PubMed

Pauly, Markus; Asendorf, Thomas; Konietschke, Frank

2016-11-01

We investigate rank-based studentized permutation methods for the nonparametric Behrens-Fisher problem, that is, inference methods for the area under the ROC curve. We hereby prove that the studentized permutation distribution of the Brunner-Munzel rank statistic is asymptotically standard normal, even under the alternative. Thus, incidentally providing the hitherto missing theoretical foundation for the Neubert and Brunner studentized permutation test. In particular, we do not only show its consistency, but also that confidence intervals for the underlying treatment effects can be computed by inverting this permutation test. In addition, we derive permutation-based range-preserving confidence intervals. Extensive simulation studies show that the permutation-based confidence intervals appear to maintain the preassigned coverage probability quite accurately (even for rather small sample sizes). For a convenient application of the proposed methods, a freely available software package for the statistical software R has been developed. A real data example illustrates the application. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Arbuscular mycorrhizal fungi inoculation mediated changes in rhizosphere bacterial community structure while promoting revegetation in a semiarid ecosystem.

PubMed

Rodríguez-Caballero, G; Caravaca, F; Fernández-González, A J; Alguacil, M M; Fernández-López, M; Roldán, A

2017-04-15

The main goal of this study was to assess the effect of the inoculation of four autochthonous shrub species with the arbuscular mycorrhizal (AM) fungus Rhizophagus intraradices on the rhizosphere bacterial community and to ascertain whether such an effect is dependent on the host plant species. Additionally, analysis of rhizosphere soil chemical and biochemical properties was performed to find relationships between them and the rhizosphere bacterial communities. Non-metric multidimensional scaling analysis and subsequent permutational multivariate analysis of variance revealed differences in bacterial community composition and structure between non-inoculated and inoculated rhizospheres. Moreover, an influence of the plant species was observed. Different bacterial groups were found to be indicator taxonomic groups of non-inoculated and inoculated rhizospheres, Gemmatimonadetes and Anaerolineaceae, respectively, being the most notable indicators. As shown by distance based redundancy analysis, the shifts in bacterial community composition and structure mediated by the inoculation with the AM fungus were mainly related to changes in plant nutrients and growth parameters, such as the shoot phosphorus content. Our findings suggest that the AM fungal inoculum was able to modify the rhizosphere bacterial community assemblage while improving the host plant performance. Copyright © 2017 Elsevier B.V. All rights reserved.

Chemometric and biological validation of a capillary electrophoresis metabolomic experiment of Schistosoma mansoni infection in mice.

PubMed

Garcia-Perez, Isabel; Angulo, Santiago; Utzinger, Jürg; Holmes, Elaine; Legido-Quigley, Cristina; Barbas, Coral

2010-07-01

Metabonomic and metabolomic studies are increasingly utilized for biomarker identification in different fields, including biology of infection. The confluence of improved analytical platforms and the availability of powerful multivariate analysis software have rendered the multiparameter profiles generated by these omics platforms a user-friendly alternative to the established analysis methods where the quality and practice of a procedure is well defined. However, unlike traditional assays, validation methods for these new multivariate profiling tools have yet to be established. We propose a validation for models obtained by CE fingerprinting of urine from mice infected with the blood fluke Schistosoma mansoni. We have analysed urine samples from two sets of mice infected in an inter-laboratory experiment where different infection methods and animal husbandry procedures were employed in order to establish the core biological response to a S. mansoni infection. CE data were analysed using principal component analysis. Validation of the scores consisted of permutation scrambling (100 repetitions) and a manual validation method, using a third of the samples (not included in the model) as a test or prediction set. The validation yielded 100% specificity and 100% sensitivity, demonstrating the robustness of these models with respect to deciphering metabolic perturbations in the mouse due to a S. mansoni infection. A total of 20 metabolites across the two experiments were identified that significantly discriminated between S. mansoni-infected and noninfected control samples. Only one of these metabolites, allantoin, was identified as manifesting different behaviour in the two experiments. This study shows the reproducibility of CE-based metabolic profiling methods for disease characterization and screening and highlights the importance of much needed validation strategies in the emerging field of metabolomics.

Wildland Arson as Clandestine Resource Management: A Space-Time Permutation Analysis and Classification of Informal Fire Management Regimes in Georgia, USA

NASA Astrophysics Data System (ADS)

Coughlan, Michael R.

2016-05-01

Forest managers are increasingly recognizing the value of disturbance-based land management techniques such as prescribed burning. Unauthorized, "arson" fires are common in the southeastern United States where a legacy of agrarian cultural heritage persists amidst an increasingly forest-dominated landscape. This paper reexamines unauthorized fire-setting in the state of Georgia, USA from a historical ecology perspective that aims to contribute to historically informed, disturbance-based land management. A space-time permutation analysis is employed to discriminate systematic, management-oriented unauthorized fires from more arbitrary or socially deviant fire-setting behaviors. This paper argues that statistically significant space-time clusters of unauthorized fire occurrence represent informal management regimes linked to the legacy of traditional land management practices. Recent scholarship has pointed out that traditional management has actively promoted sustainable resource use and, in some cases, enhanced biodiversity often through the use of fire. Despite broad-scale displacement of traditional management during the 20th century, informal management practices may locally circumvent more formal and regionally dominant management regimes. Space-time permutation analysis identified 29 statistically significant fire regimes for the state of Georgia. The identified regimes are classified by region and land cover type and their implications for historically informed disturbance-based resource management are discussed.

A permutation-based non-parametric analysis of CRISPR screen data.

PubMed

Jia, Gaoxiang; Wang, Xinlei; Xiao, Guanghua

2017-07-19

Clustered regularly-interspaced short palindromic repeats (CRISPR) screens are usually implemented in cultured cells to identify genes with critical functions. Although several methods have been developed or adapted to analyze CRISPR screening data, no single specific algorithm has gained popularity. Thus, rigorous procedures are needed to overcome the shortcomings of existing algorithms. We developed a Permutation-Based Non-Parametric Analysis (PBNPA) algorithm, which computes p-values at the gene level by permuting sgRNA labels, and thus it avoids restrictive distributional assumptions. Although PBNPA is designed to analyze CRISPR data, it can also be applied to analyze genetic screens implemented with siRNAs or shRNAs and drug screens. We compared the performance of PBNPA with competing methods on simulated data as well as on real data. PBNPA outperformed recent methods designed for CRISPR screen analysis, as well as methods used for analyzing other functional genomics screens, in terms of Receiver Operating Characteristics (ROC) curves and False Discovery Rate (FDR) control for simulated data under various settings. Remarkably, the PBNPA algorithm showed better consistency and FDR control on published real data as well. PBNPA yields more consistent and reliable results than its competitors, especially when the data quality is low. R package of PBNPA is available at: https://cran.r-project.org/web/packages/PBNPA/ .

Wildland Arson as Clandestine Resource Management: A Space-Time Permutation Analysis and Classification of Informal Fire Management Regimes in Georgia, USA.

PubMed

Coughlan, Michael R

2016-05-01

Forest managers are increasingly recognizing the value of disturbance-based land management techniques such as prescribed burning. Unauthorized, "arson" fires are common in the southeastern United States where a legacy of agrarian cultural heritage persists amidst an increasingly forest-dominated landscape. This paper reexamines unauthorized fire-setting in the state of Georgia, USA from a historical ecology perspective that aims to contribute to historically informed, disturbance-based land management. A space-time permutation analysis is employed to discriminate systematic, management-oriented unauthorized fires from more arbitrary or socially deviant fire-setting behaviors. This paper argues that statistically significant space-time clusters of unauthorized fire occurrence represent informal management regimes linked to the legacy of traditional land management practices. Recent scholarship has pointed out that traditional management has actively promoted sustainable resource use and, in some cases, enhanced biodiversity often through the use of fire. Despite broad-scale displacement of traditional management during the 20th century, informal management practices may locally circumvent more formal and regionally dominant management regimes. Space-time permutation analysis identified 29 statistically significant fire regimes for the state of Georgia. The identified regimes are classified by region and land cover type and their implications for historically informed disturbance-based resource management are discussed.

An AUC-based permutation variable importance measure for random forests

PubMed Central

2013-01-01

Background The random forest (RF) method is a commonly used tool for classification with high dimensional data as well as for ranking candidate predictors based on the so-called random forest variable importance measures (VIMs). However the classification performance of RF is known to be suboptimal in case of strongly unbalanced data, i.e. data where response class sizes differ considerably. Suggestions were made to obtain better classification performance based either on sampling procedures or on cost sensitivity analyses. However to our knowledge the performance of the VIMs has not yet been examined in the case of unbalanced response classes. In this paper we explore the performance of the permutation VIM for unbalanced data settings and introduce an alternative permutation VIM based on the area under the curve (AUC) that is expected to be more robust towards class imbalance. Results We investigated the performance of the standard permutation VIM and of our novel AUC-based permutation VIM for different class imbalance levels using simulated data and real data. The results suggest that the new AUC-based permutation VIM outperforms the standard permutation VIM for unbalanced data settings while both permutation VIMs have equal performance for balanced data settings. Conclusions The standard permutation VIM loses its ability to discriminate between associated predictors and predictors not associated with the response for increasing class imbalance. It is outperformed by our new AUC-based permutation VIM for unbalanced data settings, while the performance of both VIMs is very similar in the case of balanced classes. The new AUC-based VIM is implemented in the R package party for the unbiased RF variant based on conditional inference trees. The codes implementing our study are available from the companion website: http://www.ibe.med.uni-muenchen.de/organisation/mitarbeiter/070_drittmittel/janitza/index.html. PMID:23560875

An AUC-based permutation variable importance measure for random forests.

PubMed

Janitza, Silke; Strobl, Carolin; Boulesteix, Anne-Laure

2013-04-05

The random forest (RF) method is a commonly used tool for classification with high dimensional data as well as for ranking candidate predictors based on the so-called random forest variable importance measures (VIMs). However the classification performance of RF is known to be suboptimal in case of strongly unbalanced data, i.e. data where response class sizes differ considerably. Suggestions were made to obtain better classification performance based either on sampling procedures or on cost sensitivity analyses. However to our knowledge the performance of the VIMs has not yet been examined in the case of unbalanced response classes. In this paper we explore the performance of the permutation VIM for unbalanced data settings and introduce an alternative permutation VIM based on the area under the curve (AUC) that is expected to be more robust towards class imbalance. We investigated the performance of the standard permutation VIM and of our novel AUC-based permutation VIM for different class imbalance levels using simulated data and real data. The results suggest that the new AUC-based permutation VIM outperforms the standard permutation VIM for unbalanced data settings while both permutation VIMs have equal performance for balanced data settings. The standard permutation VIM loses its ability to discriminate between associated predictors and predictors not associated with the response for increasing class imbalance. It is outperformed by our new AUC-based permutation VIM for unbalanced data settings, while the performance of both VIMs is very similar in the case of balanced classes. The new AUC-based VIM is implemented in the R package party for the unbiased RF variant based on conditional inference trees. The codes implementing our study are available from the companion website: http://www.ibe.med.uni-muenchen.de/organisation/mitarbeiter/070_drittmittel/janitza/index.html.

Practice and Learning: Spatiotemporal Differences in Thalamo-Cortical-Cerebellar Networks Engagement across Learning Phases in Schizophrenia.

PubMed

Korostil, Michele; Remington, Gary; McIntosh, Anthony Randal

2016-01-01

Understanding how practice mediates the transition of brain-behavior networks between early and later stages of learning is constrained by the common approach to analysis of fMRI data. Prior imaging studies have mostly relied on a single scan, and parametric, task-related analyses. Our experiment incorporates a multisession fMRI lexicon-learning experiment with multivariate, whole-brain analysis to further knowledge of the distributed networks supporting practice-related learning in schizophrenia (SZ). Participants with SZ were compared with healthy control (HC) participants as they learned a novel lexicon during two fMRI scans over a several day period. All participants were trained to equal task proficiency prior to scanning. Behavioral-Partial Least Squares, a multivariate analytic approach, was used to analyze the imaging data. Permutation testing was used to determine statistical significance and bootstrap resampling to determine the reliability of the findings. With practice, HC participants transitioned to a brain-accuracy network incorporating dorsostriatal regions in late-learning stages. The SZ participants did not transition to this pattern despite comparable behavioral results. Instead, successful learners with SZ were differentiated primarily on the basis of greater engagement of perceptual and perceptual-integration brain regions. There is a different spatiotemporal unfolding of brain-learning relationships in SZ. In SZ, given the same amount of practice, the movement from networks suggestive of effortful learning toward subcortically driven procedural one differs from HC participants. Learning performance in SZ is driven by varying levels of engagement in perceptual regions, which suggests perception itself is impaired and may impact downstream, "higher level" cognition.

Circular permutant GFP insertion folding reporters

DOEpatents

Waldo, Geoffrey S [Santa Fe, NM; Cabantous, Stephanie [Los Alamos, NM

2008-06-24

Provided are methods of assaying and improving protein folding using circular permutants of fluorescent proteins, including circular permutants of GFP variants and combinations thereof. The invention further provides various nucleic acid molecules and vectors incorporating such nucleic acid molecules, comprising polynucleotides encoding fluorescent protein circular permutants derived from superfolder GFP, which polynucleotides include an internal cloning site into which a heterologous polynucleotide may be inserted in-frame with the circular permutant coding sequence, and which when expressed are capable of reporting on the degree to which a polypeptide encoded by such an inserted heterologous polynucleotide is correctly folded by correlation with the degree of fluorescence exhibited.

Circular permutant GFP insertion folding reporters

DOEpatents

Waldo, Geoffrey S; Cabantous, Stephanie

2013-02-12

Provided are methods of assaying and improving protein folding using circular permutants of fluorescent proteins, including circular permutants of GFP variants and combinations thereof. The invention further provides various nucleic acid molecules and vectors incorporating such nucleic acid molecules, comprising polynucleotides encoding fluorescent protein circular permutants derived from superfolder GFP, which polynucleotides include an internal cloning site into which a heterologous polynucleotide may be inserted in-frame with the circular permutant coding sequence, and which when expressed are capable of reporting on the degree to which a polypeptide encoded by such an inserted heterologous polynucleotide is correctly folded by correlation with the degree of fluorescence exhibited.

Circular permutant GFP insertion folding reporters

DOEpatents

Waldo, Geoffrey S [Santa Fe, NM; Cabantous, Stephanie [Los Alamos, NM

2011-06-14

Provided are methods of assaying and improving protein folding using circular permutants of fluorescent proteins, including circular permutants of GFP variants and combinations thereof. The invention further provides various nucleic acid molecules and vectors incorporating such nucleic acid molecules, comprising polynucleotides encoding fluorescent protein circular permutants derived from superfolder GFP, which polynucleotides include an internal cloning site into which a heterologous polynucleotide may be inserted in-frame with the circular permutant coding sequence, and which when expressed are capable of reporting on the degree to which a polypeptide encoded by such an inserted heterologous polynucleotide is correctly folded by correlation with the degree of fluorescence exhibited.

Circular permutant GFP insertion folding reporters

DOEpatents

Waldo, Geoffrey S.; Cabantous, Stephanie

2013-04-16

Provided are methods of assaying and improving protein folding using circular permutants of fluorescent proteins, including circular permutants of GFP variants and combinations thereof. The invention further provides various nucleic acid molecules and vectors incorporating such nucleic acid molecules, comprising polynucleotides encoding fluorescent protein circular permutants derived from superfolder GFP, which polynucleotides include an internal cloning site into which a heterologous polynucleotide may be inserted in-frame with the circular permutant coding sequence, and which when expressed are capable of reporting on the degree to which a polypeptide encoded by such an inserted heterologous polynucleotide is correctly folded by correlation with the degree of fluorescence exhibited.

Parsing the roles of the frontal lobes and basal ganglia in task control using multivoxel pattern analysis

PubMed Central

Kehagia, Angie A.; Ye, Rong; Joyce, Dan W.; Doyle, Orla M.; Rowe, James B.; Robbins, Trevor W.

2017-01-01

Cognitive control has traditionally been associated with the prefrontal cortex, based on observations of deficits in patients with frontal lesions. However, evidence from patients with Parkinson’s disease (PD) indicates that subcortical regions also contribute to control under certain conditions. We scanned 17 healthy volunteers while they performed a task switching paradigm that previously dissociated performance deficits arising from frontal lesions in comparison with PD, as a function of the abstraction of the rules that are switched. From a multivoxel pattern analysis by Gaussian Process Classification (GPC), we then estimated the forward (generative) model to infer regional patterns of activity that predict Switch / Repeat behaviour between rule conditions. At 1000 permutations, Switch / Repeat classification accuracy for concrete rules was significant in the basal ganglia, but at chance in the frontal lobe. The inverse pattern was obtained for abstract rules, whereby the conditions were successfully discriminated in the frontal lobe but not in the basal ganglia. This double dissociation highlights the difference between cortical and subcortical contributions to cognitive control and demonstrates the utility of multivariate approaches in investigations of functions that rely on distributed and overlapping neural substrates. PMID:28387585

Multiscale permutation entropy analysis of electrocardiogram

NASA Astrophysics Data System (ADS)

Liu, Tiebing; Yao, Wenpo; Wu, Min; Shi, Zhaorong; Wang, Jun; Ning, Xinbao

2017-04-01

To make a comprehensive nonlinear analysis to ECG, multiscale permutation entropy (MPE) was applied to ECG characteristics extraction to make a comprehensive nonlinear analysis of ECG. Three kinds of ECG from PhysioNet database, congestive heart failure (CHF) patients, healthy young and elderly subjects, are applied in this paper. We set embedding dimension to 4 and adjust scale factor from 2 to 100 with a step size of 2, and compare MPE with multiscale entropy (MSE). As increase of scale factor, MPE complexity of the three ECG signals are showing first-decrease and last-increase trends. When scale factor is between 10 and 32, complexities of the three ECG had biggest difference, entropy of the elderly is 0.146 less than the CHF patients and 0.025 larger than the healthy young in average, in line with normal physiological characteristics. Test results showed that MPE can effectively apply in ECG nonlinear analysis, and can effectively distinguish different ECG signals.

Image encryption using a synchronous permutation-diffusion technique

NASA Astrophysics Data System (ADS)

Enayatifar, Rasul; Abdullah, Abdul Hanan; Isnin, Ismail Fauzi; Altameem, Ayman; Lee, Malrey

2017-03-01

In the past decade, the interest on digital images security has been increased among scientists. A synchronous permutation and diffusion technique is designed in order to protect gray-level image content while sending it through internet. To implement the proposed method, two-dimensional plain-image is converted to one dimension. Afterward, in order to reduce the sending process time, permutation and diffusion steps for any pixel are performed in the same time. The permutation step uses chaotic map and deoxyribonucleic acid (DNA) to permute a pixel, while diffusion employs DNA sequence and DNA operator to encrypt the pixel. Experimental results and extensive security analyses have been conducted to demonstrate the feasibility and validity of this proposed image encryption method.

Design of an image encryption scheme based on a multiple chaotic map

NASA Astrophysics Data System (ADS)

Tong, Xiao-Jun

2013-07-01

In order to solve the problem that chaos is degenerated in limited computer precision and Cat map is the small key space, this paper presents a chaotic map based on topological conjugacy and the chaotic characteristics are proved by Devaney definition. In order to produce a large key space, a Cat map named block Cat map is also designed for permutation process based on multiple-dimensional chaotic maps. The image encryption algorithm is based on permutation-substitution, and each key is controlled by different chaotic maps. The entropy analysis, differential analysis, weak-keys analysis, statistical analysis, cipher random analysis, and cipher sensibility analysis depending on key and plaintext are introduced to test the security of the new image encryption scheme. Through the comparison to the proposed scheme with AES, DES and Logistic encryption methods, we come to the conclusion that the image encryption method solves the problem of low precision of one dimensional chaotic function and has higher speed and higher security.

Permutation glass.

PubMed

Williams, Mobolaji

2018-01-01

The field of disordered systems in statistical physics provides many simple models in which the competing influences of thermal and nonthermal disorder lead to new phases and nontrivial thermal behavior of order parameters. In this paper, we add a model to the subject by considering a disordered system where the state space consists of various orderings of a list. As in spin glasses, the disorder of such "permutation glasses" arises from a parameter in the Hamiltonian being drawn from a distribution of possible values, thus allowing nominally "incorrect orderings" to have lower energies than "correct orderings" in the space of permutations. We analyze a Gaussian, uniform, and symmetric Bernoulli distribution of energy costs, and, by employing Jensen's inequality, derive a simple condition requiring the permutation glass to always transition to the correctly ordered state at a temperature lower than that of the nondisordered system, provided that this correctly ordered state is accessible. We in turn find that in order for the correctly ordered state to be accessible, the probability that an incorrectly ordered component is energetically favored must be less than the inverse of the number of components in the system. We show that all of these results are consistent with a replica symmetric ansatz of the system. We conclude by arguing that there is no distinct permutation glass phase for the simplest model considered here and by discussing how to extend the analysis to more complex Hamiltonians capable of novel phase behavior and replica symmetry breaking. Finally, we outline an apparent correspondence between the presented system and a discrete-energy-level fermion gas. In all, the investigation introduces a class of exactly soluble models into statistical mechanics and provides a fertile ground to investigate statistical models of disorder.

Biometric identification of capillariid eggs from archaeological sites in Patagonia.

PubMed

Taglioretti, V; Fugassa, M H; Beltrame, M O; Sardella, N H

2014-06-01

Numerous eggs of capillariid nematodes have been found in coprolites from a wide range of hosts and in raptor pellets in archaeological samples from Patagonia. The structure and sculpture of the eggshell of these nematodes and their biometry are commonly used for identification. The aim of this study was to determine whether eggs of the genus Calodium with similar morphology, found in different archaeological samples from Patagonia, belong to the same species. For this purpose, capillariid eggs (N= 843) with thick walls and radial striations were studied by permutational multivariate analysis of variance (PERMANOVA). Eggs exhibiting similar shape and structure also showed similar biometry, regardless of the zoological origin of coprolites (P= 0.84), host diet (P= 0.19), character of the archaeological sites (P= 0.67) and chronology (P= 0.66). Thus, they were attributed to the same species. We suggest that an unidentified zoonotic species of the genus Calodium occurred in the digestive tract of a wide range of hosts in Patagonia during the Holocene and that both human and animal populations were exposed to this parasite during the Holocene in the study area.

Overlap Cycles for Permutations: Necessary and Sufficient Conditions

DTIC Science & Technology

2013-09-19

for Weak Orders, To appear in SIAM Journal of Discrete Math . [9] G. Hurlbert and G. Isaak, Equivalence class universal cycles for permutations, Discrete ... Math . 149 (1996), pp. 123–129. [10] J. R. Johnson, Universal cycles for permutations, Discrete Math . 309 (2009), pp. 5264– 5270. [11] E. A. Ragland

Genetic polymorphisms and the risk of stroke after cardiac surgery.

PubMed

Grocott, Hilary P; White, William D; Morris, Richard W; Podgoreanu, Mihai V; Mathew, Joseph P; Nielsen, Dahlia M; Schwinn, Debra A; Newman, Mark F

2005-09-01

Stroke represents a significant cause of morbidity and mortality after cardiac surgery. Although the risk of stroke varies according to both patient and procedural factors, the impact of genetic variants on stroke risk is not well understood. Therefore, we tested the hypothesis that specific genetic polymorphisms are associated with an increased risk of stroke after cardiac surgery. Patients undergoing cardiac surgery utilizing cardiopulmonary bypass surgery were studied. DNA was isolated from preoperative blood and analyzed for 26 different single-nucleotide polymorphisms. Multivariable logistic regression modeling was used to determine the association of clinical and genetic characteristics with stroke. Permutation analysis was used to adjust for multiple comparisons inherent in genetic association studies. A total of 1635 patients experiencing 28 strokes (1.7%) were included in the final genetic model. The combination of the 2 minor alleles of C-reactive protein (CRP; 3'UTR 1846C/T) and interleukin-6 (IL-6; -174G/C) polymorphisms, occurring in 583 (35.7%) patients, was significantly associated with stroke (odds ratio, 3.3; 95% CI, 1.4 to 8.1; P=0.0023). In a multivariable logistic model adjusting for age, the CRP and IL-6 single-nucleotide polymorphism combination remained significantly associated with stroke (P=0.0020). We demonstrate that common genetic variants of CRP (3'UTR 1846C/T) and IL-6 (-174G/C) are significantly associated with the risk of stroke after cardiac surgery, suggesting a pivotal role of inflammation in post-cardiac surgery stroke.

Randomization in cancer clinical trials: permutation test and development of a computer program.

PubMed Central

Ohashi, Y

1990-01-01

When analyzing cancer clinical trial data where the treatment allocation is done using dynamic balancing methods such as the minimization method for balancing the distribution of important prognostic factors in each arm, conservativeness occurs if such a randomization scheme is ignored and a simple unstratified analysis is carried out. In this paper, the above conservativeness is demonstrated by computer simulation, and the development of a computer program that carries out permutation tests of the log-rank statistics for clinical trial data where the allocation is done by the minimization method or a stratified permuted block design is introduced. We are planning to use this program in practice to supplement a usual stratified analysis and model-based methods such as the Cox regression. The most serious problem in cancer clinical trials in Japan is how to carry out the quality control or data management in trials that are initiated and conducted by researchers without support from pharmaceutical companies. In the final section of this paper, one international collaborative work for developing international guidelines on data management in clinical trials of bladder cancer is briefly introduced, and the differences between the system adopted in US/European statistical centers and the Japanese system is described. PMID:2269216

Development of the Nasopharyngeal Microbiota in Infants with Cystic Fibrosis.

PubMed

Prevaes, Sabine M P J; de Winter-de Groot, Karin M; Janssens, Hettie M; de Steenhuijsen Piters, Wouter A A; Tramper-Stranders, Gerdien A; Wyllie, Anne L; Hasrat, Raiza; Tiddens, Harm A; van Westreenen, Mireille; van der Ent, Cornelis K; Sanders, Elisabeth A M; Bogaert, Debby

2016-03-01

Cystic fibrosis (CF) is characterized by early structural lung disease caused by pulmonary infections. The nasopharynx of infants is a major ecological reservoir of potential respiratory pathogens. To investigate the development of nasopharyngeal microbiota profiles in infants with CF compared with those of healthy control subjects during the first 6 months of life. We conducted a prospective cohort study, from the time of diagnosis onward, in which we collected questionnaires and 324 nasopharynx samples from 20 infants with CF and 45 age-matched healthy control subjects. Microbiota profiles were characterized by 16S ribosomal RNA-based sequencing. We observed significant differences in microbial community composition (P < 0.0002 by permutational multivariate analysis of variance) and development between groups. In infants with CF, early Staphylococcus aureus and, to a lesser extent, Corynebacterium spp. and Moraxella spp. dominance were followed by a switch to Streptococcus mitis predominance after 3 months of age. In control subjects, Moraxella spp. enrichment occurred throughout the first 6 months of life. In a multivariate analysis, S. aureus, S. mitis, Corynebacterium accolens, and bacilli were significantly more abundant in infants with CF, whereas Moraxella spp., Corynebacterium pseudodiphtericum and Corynebacterium propinquum and Haemophilus influenzae were significantly more abundant in control subjects, after correction for age, antibiotic use, and respiratory symptoms. Antibiotic use was independently associated with increased colonization of gram-negative bacteria such as Burkholderia spp. and members of the Enterobacteriaceae bacteria family and reduced colonization of potential beneficial commensals. From diagnosis onward, we observed distinct patterns of nasopharyngeal microbiota development in infants with CF under 6 months of age compared with control subjects and a marked effect of antibiotic therapy leading toward a gram-negative microbial composition.

Using R to Simulate Permutation Distributions for Some Elementary Experimental Designs

ERIC Educational Resources Information Center

Eudey, T. Lynn; Kerr, Joshua D.; Trumbo, Bruce E.

2010-01-01

Null distributions of permutation tests for two-sample, paired, and block designs are simulated using the R statistical programming language. For each design and type of data, permutation tests are compared with standard normal-theory and nonparametric tests. These examples (often using real data) provide for classroom discussion use of metrics…

Circular permutation of a WW domain: Folding still occurs after excising the turn of the folding-nucleating hairpin

PubMed Central

Kier, Brandon L.; Anderson, Jordan M.; Andersen, Niels H.

2014-01-01

A hyperstable Pin1 WW domain has been circularly permuted via excision of the fold-nucleating turn; it still folds to form the native three-strand sheet and hydrophobic core features. Multiprobe folding dynamics studies of the normal and circularly permuted sequences, as well as their constituent hairpin fragments and comparable-length β-strand-loop-β-strand models, indicate 2-state folding for all topologies. N-terminal hairpin formation is the fold nucleating event for the wild-type sequence; the slower folding circular permutant has a more distributed folding transition state. PMID:24350581

Integrated Analysis of Pharmacologic, Clinical, and SNP Microarray Data using Projection onto the Most Interesting Statistical Evidence with Adaptive Permutation Testing

PubMed Central

Pounds, Stan; Cao, Xueyuan; Cheng, Cheng; Yang, Jun; Campana, Dario; Evans, William E.; Pui, Ching-Hon; Relling, Mary V.

2010-01-01

Powerful methods for integrated analysis of multiple biological data sets are needed to maximize interpretation capacity and acquire meaningful knowledge. We recently developed Projection Onto the Most Interesting Statistical Evidence (PROMISE). PROMISE is a statistical procedure that incorporates prior knowledge about the biological relationships among endpoint variables into an integrated analysis of microarray gene expression data with multiple biological and clinical endpoints. Here, PROMISE is adapted to the integrated analysis of pharmacologic, clinical, and genome-wide genotype data that incorporating knowledge about the biological relationships among pharmacologic and clinical response data. An efficient permutation-testing algorithm is introduced so that statistical calculations are computationally feasible in this higher-dimension setting. The new method is applied to a pediatric leukemia data set. The results clearly indicate that PROMISE is a powerful statistical tool for identifying genomic features that exhibit a biologically meaningful pattern of association with multiple endpoint variables. PMID:21516175

Cipher image damage and decisions in real time

NASA Astrophysics Data System (ADS)

Silva-García, Victor Manuel; Flores-Carapia, Rolando; Rentería-Márquez, Carlos; Luna-Benoso, Benjamín; Jiménez-Vázquez, Cesar Antonio; González-Ramírez, Marlon David

2015-01-01

This paper proposes a method for constructing permutations on m position arrangements. Our objective is to encrypt color images using advanced encryption standard (AES), using variable permutations means a different one for each 128-bit block in the first round after the x-or operation is applied. Furthermore, this research offers the possibility of knowing the original image when the encrypted figure suffered a failure from either an attack or not. This is achieved by permuting the original image pixel positions before being encrypted with AES variable permutations, which means building a pseudorandom permutation of 250,000 position arrays or more. To this end, an algorithm that defines a bijective function between the nonnegative integer and permutation sets is built. From this algorithm, the way to build permutations on the 0,1,…,m-1 array, knowing m-1 constants, is presented. The transcendental numbers are used to select these m-1 constants in a pseudorandom way. The quality of the proposed encryption according to the following criteria is evaluated: the correlation coefficient, the entropy, and the discrete Fourier transform. A goodness-of-fit test for each basic color image is proposed to measure the bits randomness degree of the encrypted figure. On the other hand, cipher images are obtained in a loss-less encryption way, i.e., no JPEG file formats are used.

Set-Based Discrete Particle Swarm Optimization Based on Decomposition for Permutation-Based Multiobjective Combinatorial Optimization Problems.

PubMed

Yu, Xue; Chen, Wei-Neng; Gu, Tianlong; Zhang, Huaxiang; Yuan, Huaqiang; Kwong, Sam; Zhang, Jun

2018-07-01

This paper studies a specific class of multiobjective combinatorial optimization problems (MOCOPs), namely the permutation-based MOCOPs. Many commonly seen MOCOPs, e.g., multiobjective traveling salesman problem (MOTSP), multiobjective project scheduling problem (MOPSP), belong to this problem class and they can be very different. However, as the permutation-based MOCOPs share the inherent similarity that the structure of their search space is usually in the shape of a permutation tree, this paper proposes a generic multiobjective set-based particle swarm optimization methodology based on decomposition, termed MS-PSO/D. In order to coordinate with the property of permutation-based MOCOPs, MS-PSO/D utilizes an element-based representation and a constructive approach. Through this, feasible solutions under constraints can be generated step by step following the permutation-tree-shaped structure. And problem-related heuristic information is introduced in the constructive approach for efficiency. In order to address the multiobjective optimization issues, the decomposition strategy is employed, in which the problem is converted into multiple single-objective subproblems according to a set of weight vectors. Besides, a flexible mechanism for diversity control is provided in MS-PSO/D. Extensive experiments have been conducted to study MS-PSO/D on two permutation-based MOCOPs, namely the MOTSP and the MOPSP. Experimental results validate that the proposed methodology is promising.

Intrinsically bent DNA in replication origins and gene promoters.

PubMed

Gimenes, F; Takeda, K I; Fiorini, A; Gouveia, F S; Fernandez, M A

2008-06-24

Intrinsically bent DNA is an alternative conformation of the DNA molecule caused by the presence of dA/dT tracts, 2 to 6 bp long, in a helical turn phase DNA or with multiple intervals of 10 to 11 bp. Other than flexibility, intrinsic bending sites induce DNA curvature in particular chromosome regions such as replication origins and promoters. Intrinsically bent DNA sites are important in initiating DNA replication, and are sometimes found near to regions associated with the nuclear matrix. Many methods have been developed to localize bent sites, for example, circular permutation, computational analysis, and atomic force microscopy. This review discusses intrinsically bent DNA sites associated with replication origins and gene promoter regions in prokaryote and eukaryote cells. We also describe methods for identifying bent DNA sites for circular permutation and computational analysis.

Linear models: permutation methods

USGS Publications Warehouse

Cade, B.S.; Everitt, B.S.; Howell, D.C.

2005-01-01

Permutation tests (see Permutation Based Inference) for the linear model have applications in behavioral studies when traditional parametric assumptions about the error term in a linear model are not tenable. Improved validity of Type I error rates can be achieved with properly constructed permutation tests. Perhaps more importantly, increased statistical power, improved robustness to effects of outliers, and detection of alternative distributional differences can be achieved by coupling permutation inference with alternative linear model estimators. For example, it is well-known that estimates of the mean in linear model are extremely sensitive to even a single outlying value of the dependent variable compared to estimates of the median [7, 19]. Traditionally, linear modeling focused on estimating changes in the center of distributions (means or medians). However, quantile regression allows distributional changes to be estimated in all or any selected part of a distribution or responses, providing a more complete statistical picture that has relevance to many biological questions [6]...

Permutation-invariant distance between atomic configurations

NASA Astrophysics Data System (ADS)

Ferré, Grégoire; Maillet, Jean-Bernard; Stoltz, Gabriel

2015-09-01

We present a permutation-invariant distance between atomic configurations, defined through a functional representation of atomic positions. This distance enables us to directly compare different atomic environments with an arbitrary number of particles, without going through a space of reduced dimensionality (i.e., fingerprints) as an intermediate step. Moreover, this distance is naturally invariant through permutations of atoms, avoiding the time consuming associated minimization required by other common criteria (like the root mean square distance). Finally, the invariance through global rotations is accounted for by a minimization procedure in the space of rotations solved by Monte Carlo simulated annealing. A formal framework is also introduced, showing that the distance we propose verifies the property of a metric on the space of atomic configurations. Two examples of applications are proposed. The first one consists in evaluating faithfulness of some fingerprints (or descriptors), i.e., their capacity to represent the structural information of a configuration. The second application concerns structural analysis, where our distance proves to be efficient in discriminating different local structures and even classifying their degree of similarity.

Hurdles and sorting by inversions: combinatorial, statistical, and experimental results.

PubMed

Swenson, Krister M; Lin, Yu; Rajan, Vaibhav; Moret, Bernard M E

2009-10-01

As data about genomic architecture accumulates, genomic rearrangements have attracted increasing attention. One of the main rearrangement mechanisms, inversions (also called reversals), was characterized by Hannenhalli and Pevzner and this characterization in turn extended by various authors. The characterization relies on the concepts of breakpoints, cycles, and obstructions colorfully named hurdles and fortresses. In this paper, we study the probability of generating a hurdle in the process of sorting a permutation if one does not take special precautions to avoid them (as in a randomized algorithm, for instance). To do this we revisit and extend the work of Caprara and of Bergeron by providing simple and exact characterizations of the probability of encountering a hurdle in a random permutation. Using similar methods we provide the first asymptotically tight analysis of the probability that a fortress exists in a random permutation. Finally, we study other aspects of hurdles, both analytically and through experiments: when are they created in a sequence of sorting inversions, how much later are they detected, and how much work may need to be undone to return to a sorting sequence.

Generalized composite multiscale permutation entropy and Laplacian score based rolling bearing fault diagnosis

NASA Astrophysics Data System (ADS)

Zheng, Jinde; Pan, Haiyang; Yang, Shubao; Cheng, Junsheng

2018-01-01

Multiscale permutation entropy (MPE) is a recently proposed nonlinear dynamic method for measuring the randomness and detecting the nonlinear dynamic change of time series and can be used effectively to extract the nonlinear dynamic fault feature from vibration signals of rolling bearing. To solve the drawback of coarse graining process in MPE, an improved MPE method called generalized composite multiscale permutation entropy (GCMPE) was proposed in this paper. Also the influence of parameters on GCMPE and its comparison with the MPE are studied by analyzing simulation data. GCMPE was applied to the fault feature extraction from vibration signal of rolling bearing and then based on the GCMPE, Laplacian score for feature selection and the Particle swarm optimization based support vector machine, a new fault diagnosis method for rolling bearing was put forward in this paper. Finally, the proposed method was applied to analyze the experimental data of rolling bearing. The analysis results show that the proposed method can effectively realize the fault diagnosis of rolling bearing and has a higher fault recognition rate than the existing methods.

BROCCOLI: Software for fast fMRI analysis on many-core CPUs and GPUs

PubMed Central

Eklund, Anders; Dufort, Paul; Villani, Mattias; LaConte, Stephen

2014-01-01

Analysis of functional magnetic resonance imaging (fMRI) data is becoming ever more computationally demanding as temporal and spatial resolutions improve, and large, publicly available data sets proliferate. Moreover, methodological improvements in the neuroimaging pipeline, such as non-linear spatial normalization, non-parametric permutation tests and Bayesian Markov Chain Monte Carlo approaches, can dramatically increase the computational burden. Despite these challenges, there do not yet exist any fMRI software packages which leverage inexpensive and powerful graphics processing units (GPUs) to perform these analyses. Here, we therefore present BROCCOLI, a free software package written in OpenCL (Open Computing Language) that can be used for parallel analysis of fMRI data on a large variety of hardware configurations. BROCCOLI has, for example, been tested with an Intel CPU, an Nvidia GPU, and an AMD GPU. These tests show that parallel processing of fMRI data can lead to significantly faster analysis pipelines. This speedup can be achieved on relatively standard hardware, but further, dramatic speed improvements require only a modest investment in GPU hardware. BROCCOLI (running on a GPU) can perform non-linear spatial normalization to a 1 mm3 brain template in 4–6 s, and run a second level permutation test with 10,000 permutations in about a minute. These non-parametric tests are generally more robust than their parametric counterparts, and can also enable more sophisticated analyses by estimating complicated null distributions. Additionally, BROCCOLI includes support for Bayesian first-level fMRI analysis using a Gibbs sampler. The new software is freely available under GNU GPL3 and can be downloaded from github (https://github.com/wanderine/BROCCOLI/). PMID:24672471

Comparative study on the gut microbiotas of four economically important Asian carp species.

PubMed

Li, Xinghao; Yu, Yuhe; Li, Chang; Yan, Qingyun

2018-05-07

Gut microbiota of four economically important Asian carp species (silver carp, Hypophthalmichthys molitrix; bighead carp, Hypophthalmichthys nobilis; grass carp, Ctenopharyngodon idella; common carp, Cyprinus carpio) were compared using 16S rRNA gene pyrosequencing. Analysis of more than 590,000 quality-filtered sequences obtained from the foregut, midgut and hindgut of these four carp species revealed high microbial diversity among the samples. The foregut samples of grass carp exhibited more than 1,600 operational taxonomy units (OTUs) and the highest alpha-diversity index, followed by the silver carp foregut and midgut. Proteobacteria, Firmicutes, Bacteroidetes and Fusobacteria were the predominant phyla regardless of fish species or gut type. Pairwise (weighted) UniFrac distance-based permutational multivariate analysis of variance with fish species as a factor produced significant association (P<0.01). The gut microbiotas of all four carp species harbored saccharolytic or proteolytic microbes, likely in response to the differences in their feeding habits. In addition, extensive variations were also observed even within the same fish species. Our results indicate that the gut microbiotas of Asian carp depend on the exact species, even when the different species were cohabiting in the same environment. This study provides some new insights into developing commercial fish feeds and improving existing aquaculture strategies.

Wing morphometrics as a possible tool for the diagnosis of the Ceratitis fasciventris, C. anonae, C. rosa complex (Diptera, Tephritidae).

PubMed

Van Cann, Joannes; Virgilio, Massimiliano; Jordaens, Kurt; De Meyer, Marc

2015-01-01

Previous attempts to resolve the Ceratitis FAR complex (Ceratitis fasciventris, Ceratitis anonae, Ceratitis rosa, Diptera, Tephritidae) showed contrasting results and revealed the occurrence of five microsatellite genotypic clusters (A, F1, F2, R1, R2). In this paper we explore the potential of wing morphometrics for the diagnosis of FAR morphospecies and genotypic clusters. We considered a set of 227 specimens previously morphologically identified and genotyped at 16 microsatellite loci. Seventeen wing landmarks and 6 wing band areas were used for morphometric analyses. Permutational multivariate analysis of variance detected significant differences both across morphospecies and genotypic clusters (for both males and females). Unconstrained and constrained ordinations did not properly resolve groups corresponding to morphospecies or genotypic clusters. However, posterior group membership probabilities (PGMPs) of the Discriminant Analysis of Principal Components (DAPC) allowed the consistent identification of a relevant proportion of specimens (but with performances differing across morphospecies and genotypic clusters). This study suggests that wing morphometrics and PGMPs might represent a possible tool for the diagnosis of species within the FAR complex. Here, we propose a tentative diagnostic method and provide a first reference library of morphometric measures that might be used for the identification of additional and unidentified FAR specimens.

Bird distributional patterns support biogeographical histories and are associated with bioclimatic units in the Atlantic Forest, Brazil.

PubMed

Carvalho, Cristiano DE Santana; Nascimento, Nayla Fábia Ferreira DO; Araujo, Helder F P DE

2017-10-17

Rivers as barriers to dispersal and past forest refugia are two of the hypotheses proposed to explain the patterns of biodiversity in the Atlantic Forest. It has recently been shown that possible past refugia correspond to bioclimatically different regions, so we tested whether patterns of shared distribution of bird taxa in the Atlantic Forest are 1) limited by the Doce and São Francisco rivers or 2) associated with the bioclimatically different southern and northeastern regions. We catalogued lists of forest birds from 45 locations, 36 in the Atlantic forest and nine in Amazon, and used parsimony analysis of endemicity to identify groups of shared taxa. We also compared differences between these groups by permutational multivariate analysis of variance and identified the species that best supported the resulting groups. The results showed that the distribution of forest birds is divided into two main regions in the Atlantic Forest, the first with more southern localities and the second with northeastern localities. This distributional pattern is not delimited by riverbanks, but it may be associated with bioclimatic units, surrogated by altitude, that maintain current environmental differences between two main regions on Atlantic Forest and may be related to phylogenetic histories of taxa supporting the two groups.

Permutation inference for the general linear model

PubMed Central

Winkler, Anderson M.; Ridgway, Gerard R.; Webster, Matthew A.; Smith, Stephen M.; Nichols, Thomas E.

2014-01-01

Permutation methods can provide exact control of false positives and allow the use of non-standard statistics, making only weak assumptions about the data. With the availability of fast and inexpensive computing, their main limitation would be some lack of flexibility to work with arbitrary experimental designs. In this paper we report on results on approximate permutation methods that are more flexible with respect to the experimental design and nuisance variables, and conduct detailed simulations to identify the best method for settings that are typical for imaging research scenarios. We present a generic framework for permutation inference for complex general linear models (glms) when the errors are exchangeable and/or have a symmetric distribution, and show that, even in the presence of nuisance effects, these permutation inferences are powerful while providing excellent control of false positives in a wide range of common and relevant imaging research scenarios. We also demonstrate how the inference on glm parameters, originally intended for independent data, can be used in certain special but useful cases in which independence is violated. Detailed examples of common neuroimaging applications are provided, as well as a complete algorithm – the “randomise” algorithm – for permutation inference with the glm. PMID:24530839

Modulation of a protein free-energy landscape by circular permutation.

PubMed

Radou, Gaël; Enciso, Marta; Krivov, Sergei; Paci, Emanuele

2013-11-07

Circular permutations usually retain the native structure and function of a protein while inevitably perturbing its folding dynamics. By using simulations with a structure-based model and a rigorous methodology to determine free-energy surfaces from trajectories, we evaluate the effect of a circular permutation on the free-energy landscape of the protein T4 lysozyme. We observe changes which, although subtle, largely affect the cooperativity between the two subdomains. Such a change in cooperativity has been previously experimentally observed and recently also characterized using single molecule optical tweezers and the Crooks relation. The free-energy landscapes show that both the wild type and circular permutant have an on-pathway intermediate, previously experimentally characterized, in which one of the subdomains is completely formed. The landscapes, however, differ in the position of the rate-limiting step for folding, which occurs before the intermediate in the wild type and after in the circular permutant. This shift of transition state explains the observed change in the cooperativity. The underlying free-energy landscape thus provides a microscopic description of the folding dynamics and the connection between circular permutation and the loss of cooperativity experimentally observed.

The Lottery Is a Mathematics Powerball

ERIC Educational Resources Information Center

Lim, Vivian; Rubel, Laurie; Shookhoff, Lauren; Sullivan, Mathew; Williams, Sarah

2016-01-01

The lottery has rich potential for mathematical explorations. It serves as a real-world context to explore concepts of permutations, combinations, sample space, and probability in terms of making sense of the lottery games. The lottery offers additional possibilities in terms of scaling, data analysis, and spatial analysis. Finally, by readily…

Permutation parity machines for neural cryptography.

PubMed

Reyes, Oscar Mauricio; Zimmermann, Karl-Heinz

2010-06-01

Recently, synchronization was proved for permutation parity machines, multilayer feed-forward neural networks proposed as a binary variant of the tree parity machines. This ability was already used in the case of tree parity machines to introduce a key-exchange protocol. In this paper, a protocol based on permutation parity machines is proposed and its performance against common attacks (simple, geometric, majority and genetic) is studied.

Inference for Distributions over the Permutation Group

DTIC Science & Technology

2008-05-01

world problems, such as voting , ranking, and data association. Representing uncertainty over permutations is challenging, since there are n...problems, such as voting , ranking, and data association. Representing uncertainty over permutations is challenging, since there are n! possibilities...the Krone ker (or Tensor ) Produ t Representation.In general, the Krone ker produ t representation is redu ible, and so it ande omposed into a dire t

Students' Errors in Solving the Permutation and Combination Problems Based on Problem Solving Steps of Polya

ERIC Educational Resources Information Center

Sukoriyanto; Nusantara, Toto; Subanji; Chandra, Tjang Daniel

2016-01-01

This article was written based on the results of a study evaluating students' errors in problem solving of permutation and combination in terms of problem solving steps according to Polya. Twenty-five students were asked to do four problems related to permutation and combination. The research results showed that the students still did a mistake in…

Permutation parity machines for neural cryptography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Reyes, Oscar Mauricio; Escuela de Ingenieria Electrica, Electronica y Telecomunicaciones, Universidad Industrial de Santander, Bucaramanga; Zimmermann, Karl-Heinz

2010-06-15

Recently, synchronization was proved for permutation parity machines, multilayer feed-forward neural networks proposed as a binary variant of the tree parity machines. This ability was already used in the case of tree parity machines to introduce a key-exchange protocol. In this paper, a protocol based on permutation parity machines is proposed and its performance against common attacks (simple, geometric, majority and genetic) is studied.

Sorting signed permutations by short operations.

PubMed

Galvão, Gustavo Rodrigues; Lee, Orlando; Dias, Zanoni

2015-01-01

During evolution, global mutations may alter the order and the orientation of the genes in a genome. Such mutations are referred to as rearrangement events, or simply operations. In unichromosomal genomes, the most common operations are reversals, which are responsible for reversing the order and orientation of a sequence of genes, and transpositions, which are responsible for switching the location of two contiguous portions of a genome. The problem of computing the minimum sequence of operations that transforms one genome into another - which is equivalent to the problem of sorting a permutation into the identity permutation - is a well-studied problem that finds application in comparative genomics. There are a number of works concerning this problem in the literature, but they generally do not take into account the length of the operations (i.e. the number of genes affected by the operations). Since it has been observed that short operations are prevalent in the evolution of some species, algorithms that efficiently solve this problem in the special case of short operations are of interest. In this paper, we investigate the problem of sorting a signed permutation by short operations. More precisely, we study four flavors of this problem: (i) the problem of sorting a signed permutation by reversals of length at most 2; (ii) the problem of sorting a signed permutation by reversals of length at most 3; (iii) the problem of sorting a signed permutation by reversals and transpositions of length at most 2; and (iv) the problem of sorting a signed permutation by reversals and transpositions of length at most 3. We present polynomial-time solutions for problems (i) and (iii), a 5-approximation for problem (ii), and a 3-approximation for problem (iv). Moreover, we show that the expected approximation ratio of the 5-approximation algorithm is not greater than 3 for random signed permutations with more than 12 elements. Finally, we present experimental results that show that the approximation ratios of the approximation algorithms cannot be smaller than 3. In particular, this means that the approximation ratio of the 3-approximation algorithm is tight.

Assessment of the Lower Urinary Tract Microbiota during Symptom Flare in Women with Urologic Chronic Pelvic Pain Syndrome: A MAPP Network Study.

PubMed

Nickel, J Curtis; Stephens, Alisa; Landis, J Richard; Mullins, Chris; van Bokhoven, Adrie; Lucia, M Scott; Ehrlich, Garth D

2016-02-01

We compared culture independent assessment of microbiota of the lower urinary tract in standard culture negative female patients with urological chronic pelvic pain syndrome who reported symptom flare vs those who did not report a flare. Initial stream (VB1) and midstream (VB2) urine specimens (233 patients with urological chronic pelvic pain syndrome) were analyzed with Ibis T-5000 Universal Biosensor system technology for comprehensive identification of microorganism species. Differences between flare and nonflare groups for presence or number of different species within a higher level group (richness) were examined by permutational multivariate analysis of variance and logistic regression. Overall 81 species (35 genera) were detected in VB1 and 73 (33) in VB2. Mean (SD) VB1 and VB2 species count per person was 2.6 (1.5) and 2.4 (1.5) for 86 flare cases and 2.8 (1.3) and 2.5 (1.5) for 127 nonflare cases, respectively. Overall the species composition did not significantly differ between flare and nonflare cases at any level (p=0.14 species, p=0.95 genus in VB1 and VB2, respectively) in multivariate analysis for richness. Univariate analysis, unadjusted as well as adjusted, confirmed a significantly greater prevalence of fungi (Candida and Saccharomyces) in the flare group (15.7%) compared to the nonflare group in VB2 (3.9%) (p=0.01). When adjusted for antibiotic use and menstrual phase, women who reported a flare remained more likely to have fungi present in VB2 specimens (OR 8.3, CI 1.7-39.4). Among women with urological chronic pelvic pain syndrome the prevalence of fungi (Candida and Saccharomyces sp.) was significantly greater in those who reported a flare compared to those who did not. Copyright © 2016 American Urological Association Education and Research, Inc. Published by Elsevier Inc. All rights reserved.

Assessment of the Lower Urinary Tract Microbiota during Symptom Flare in Women with Urologic Chronic Pelvic Pain Syndrome: A MAPP Network Study

PubMed Central

Nickel, J. Curtis; Stephens, Alisa; Landis, J. Richard; Mullins, Chris; van Bokhoven, Adrie; Lucia, M. Scott; Ehrlich, Garth D.

2016-01-01

Purpose We compared culture independent assessment of microbiota of the lower urinary tract in standard culture negative female patients with urological chronic pelvic pain syndrome who reported symptom flare vs those who did not report a flare. Materials and Methods Initial stream (VB1) and midstream (VB2) urine specimens (233 patients with urological chronic pelvic pain syndrome) were analyzed with Ibis T-5000 Universal Biosensor system technology for comprehensive identification of microorganism species. Differences between flare and nonflare groups for presence or number of different species within a higher level group (richness) were examined by permutational multivariate analysis of variance and logistic regression. Results Overall 81 species (35 genera) were detected in VB1 and 73 (33) in VB2. Mean (SD) VB1 and VB2 species count per person was 2.6 (1.5) and 2.4 (1.5) for 86 flare cases and 2.8 (1.3) and 2.5 (1.5) for 127 nonflare cases, respectively. Overall the species composition did not significantly differ between flare and nonflare cases at any level (p=0.14 species, p=0.95 genus in VB1 and VB2, respectively) in multivariate analysis for richness. Univariate analysis, unadjusted as well as adjusted, confirmed a significantly greater prevalence of fungi (Candida and Saccharomyces) in the flare group (15.7%) compared to the nonflare group in VB2 (3.9%) (p=0.01). When adjusted for antibiotic use and menstrual phase, women who reported a flare remained more likely to have fungi present in VB2 specimens (OR 8.3, CI 1.7–39.4). Conclusions Among women with urological chronic pelvic pain syndrome the prevalence of fungi (Candida and Saccharomyces sp.) was significantly greater in those who reported a flare compared to those who did not. PMID:26410734

CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab/GNU Octave.

PubMed

Oosterhof, Nikolaas N; Connolly, Andrew C; Haxby, James V

2016-01-01

Recent years have seen an increase in the popularity of multivariate pattern (MVP) analysis of functional magnetic resonance (fMRI) data, and, to a much lesser extent, magneto- and electro-encephalography (M/EEG) data. We present CoSMoMVPA, a lightweight MVPA (MVP analysis) toolbox implemented in the intersection of the Matlab and GNU Octave languages, that treats both fMRI and M/EEG data as first-class citizens. CoSMoMVPA supports all state-of-the-art MVP analysis techniques, including searchlight analyses, classification, correlations, representational similarity analysis, and the time generalization method. These can be used to address both data-driven and hypothesis-driven questions about neural organization and representations, both within and across: space, time, frequency bands, neuroimaging modalities, individuals, and species. It uses a uniform data representation of fMRI data in the volume or on the surface, and of M/EEG data at the sensor and source level. Through various external toolboxes, it directly supports reading and writing a variety of fMRI and M/EEG neuroimaging formats, and, where applicable, can convert between them. As a result, it can be integrated readily in existing pipelines and used with existing preprocessed datasets. CoSMoMVPA overloads the traditional volumetric searchlight concept to support neighborhoods for M/EEG and surface-based fMRI data, which supports localization of multivariate effects of interest across space, time, and frequency dimensions. CoSMoMVPA also provides a generalized approach to multiple comparison correction across these dimensions using Threshold-Free Cluster Enhancement with state-of-the-art clustering and permutation techniques. CoSMoMVPA is highly modular and uses abstractions to provide a uniform interface for a variety of MVP measures. Typical analyses require a few lines of code, making it accessible to beginner users. At the same time, expert programmers can easily extend its functionality. CoSMoMVPA comes with extensive documentation, including a variety of runnable demonstration scripts and analysis exercises (with example data and solutions). It uses best software engineering practices including version control, distributed development, an automated test suite, and continuous integration testing. It can be used with the proprietary Matlab and the free GNU Octave software, and it complies with open source distribution platforms such as NeuroDebian. CoSMoMVPA is Free/Open Source Software under the permissive MIT license. Website: http://cosmomvpa.org Source code: https://github.com/CoSMoMVPA/CoSMoMVPA.

CoSMoMVPA: Multi-Modal Multivariate Pattern Analysis of Neuroimaging Data in Matlab/GNU Octave

PubMed Central

Oosterhof, Nikolaas N.; Connolly, Andrew C.; Haxby, James V.

2016-01-01

Recent years have seen an increase in the popularity of multivariate pattern (MVP) analysis of functional magnetic resonance (fMRI) data, and, to a much lesser extent, magneto- and electro-encephalography (M/EEG) data. We present CoSMoMVPA, a lightweight MVPA (MVP analysis) toolbox implemented in the intersection of the Matlab and GNU Octave languages, that treats both fMRI and M/EEG data as first-class citizens. CoSMoMVPA supports all state-of-the-art MVP analysis techniques, including searchlight analyses, classification, correlations, representational similarity analysis, and the time generalization method. These can be used to address both data-driven and hypothesis-driven questions about neural organization and representations, both within and across: space, time, frequency bands, neuroimaging modalities, individuals, and species. It uses a uniform data representation of fMRI data in the volume or on the surface, and of M/EEG data at the sensor and source level. Through various external toolboxes, it directly supports reading and writing a variety of fMRI and M/EEG neuroimaging formats, and, where applicable, can convert between them. As a result, it can be integrated readily in existing pipelines and used with existing preprocessed datasets. CoSMoMVPA overloads the traditional volumetric searchlight concept to support neighborhoods for M/EEG and surface-based fMRI data, which supports localization of multivariate effects of interest across space, time, and frequency dimensions. CoSMoMVPA also provides a generalized approach to multiple comparison correction across these dimensions using Threshold-Free Cluster Enhancement with state-of-the-art clustering and permutation techniques. CoSMoMVPA is highly modular and uses abstractions to provide a uniform interface for a variety of MVP measures. Typical analyses require a few lines of code, making it accessible to beginner users. At the same time, expert programmers can easily extend its functionality. CoSMoMVPA comes with extensive documentation, including a variety of runnable demonstration scripts and analysis exercises (with example data and solutions). It uses best software engineering practices including version control, distributed development, an automated test suite, and continuous integration testing. It can be used with the proprietary Matlab and the free GNU Octave software, and it complies with open source distribution platforms such as NeuroDebian. CoSMoMVPA is Free/Open Source Software under the permissive MIT license. Website: http://cosmomvpa.org Source code: https://github.com/CoSMoMVPA/CoSMoMVPA PMID:27499741

Regional Value Analysis at Threat Evaluation

DTIC Science & Technology

2014-06-01

targets based on information entropy and fuzzy optimization theory. in Industrial Engineering and Engineering Management (IEEM), 2011 IEEE...Assignment by Virtual Permutation and Tabu Search Heuristics. Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on, 2010

Spatiotemporal Permutation Entropy as a Measure for Complexity of Cardiac Arrhythmia

NASA Astrophysics Data System (ADS)

Schlemmer, Alexander; Berg, Sebastian; Lilienkamp, Thomas; Luther, Stefan; Parlitz, Ulrich

2018-05-01

Permutation entropy (PE) is a robust quantity for measuring the complexity of time series. In the cardiac community it is predominantly used in the context of electrocardiogram (ECG) signal analysis for diagnoses and predictions with a major application found in heart rate variability parameters. In this article we are combining spatial and temporal PE to form a spatiotemporal PE that captures both, complexity of spatial structures and temporal complexity at the same time. We demonstrate that the spatiotemporal PE (STPE) quantifies complexity using two datasets from simulated cardiac arrhythmia and compare it to phase singularity analysis and spatial PE (SPE). These datasets simulate ventricular fibrillation (VF) on a two-dimensional and a three-dimensional medium using the Fenton-Karma model. We show that SPE and STPE are robust against noise and demonstrate its usefulness for extracting complexity features at different spatial scales.

Permutation methods for the structured exploratory data analysis (SEDA) of familial trait values.

PubMed

Karlin, S; Williams, P T

1984-07-01

A collection of functions that contrast familial trait values between and across generations is proposed for studying transmission effects and other collateral influences in nuclear families. Two classes of structured exploratory data analysis (SEDA) statistics are derived from ratios of these functions. SEDA-functionals are the empirical cumulative distributions of the ratio of the two contrasts computed within each family. SEDA-indices are formed by first averaging the numerator and denominator contrasts separately over the population and then forming their ratio. The significance of SEDA results are determined by a spectrum of permutation techniques that selectively shuffle the trait values across families. The process systematically alters certain family structure relationships while keeping other familial relationships intact. The methodology is applied to five data examples of plasma total cholesterol concentrations, reported height values, dermatoglyphic pattern intensity index scores, measurements of dopamine-beta-hydroxylase activity, and psychometric cognitive test results.

Determining distinct circuit in complete graphs using permutation

NASA Astrophysics Data System (ADS)

Karim, Sharmila; Ibrahim, Haslinda; Darus, Maizon Mohd

2017-11-01

A Half Butterfly Method (HBM) is a method introduced to construct the distinct circuits in complete graphs where used the concept of isomorphism. The Half Butterfly Method was applied in the field of combinatorics such as in listing permutations of n elements. However the method of determining distinct circuit using HBM for n > 4 is become tedious. Thus, in this paper, we present the method of generating distinct circuit using permutation.

A Versatile Platform for Nanotechnology Based on Circular Permutation of a Chaperonin Protein

NASA Technical Reports Server (NTRS)

Paavola, Chad; McMillan, Andrew; Trent, Jonathan; Chan, Suzanne; Mazzarella, Kellen; Li, Yi-Fen

2004-01-01

A number of protein complexes have been developed as nanoscale templates. These templates can be functionalized using the peptide sequences that bind inorganic materials. However, it is difficult to integrate peptides into a specific position within a protein template. Integrating intact proteins with desirable binding or catalytic activities is an even greater challenge. We present a general method for modifying protein templates using circular permutation so that additional peptide sequence can be added in a wide variety of specific locations. Circular permutation is a reordering of the polypeptide chain such that the original termini are joined and new termini are created elsewhere in the protein. New sequence can be joined to the protein termini without perturbing the protein structure and with minimal limitation on the size and conformation of the added sequence. We have used this approach to modify a chaperonin protein template, placing termini at five different locations distributed across the surface of the protein complex. These permutants are competent to form the double-ring structures typical of chaperonin proteins. The permuted double-rings also form the same assemblies as the unmodified protein. We fused a fluorescent protein to two representative permutants and demonstrated that it assumes its active structure and does not interfere with assembly of chaperonin double-rings.

Rank score and permutation testing alternatives for regression quantile estimates

USGS Publications Warehouse

Cade, B.S.; Richards, J.D.; Mielke, P.W.

2006-01-01

Performance of quantile rank score tests used for hypothesis testing and constructing confidence intervals for linear quantile regression estimates (0 ≤ τ ≤ 1) were evaluated by simulation for models with p = 2 and 6 predictors, moderate collinearity among predictors, homogeneous and hetero-geneous errors, small to moderate samples (n = 20–300), and central to upper quantiles (0.50–0.99). Test statistics evaluated were the conventional quantile rank score T statistic distributed as χ2 random variable with q degrees of freedom (where q parameters are constrained by H 0:) and an F statistic with its sampling distribution approximated by permutation. The permutation F-test maintained better Type I errors than the T-test for homogeneous error models with smaller n and more extreme quantiles τ. An F distributional approximation of the F statistic provided some improvements in Type I errors over the T-test for models with > 2 parameters, smaller n, and more extreme quantiles but not as much improvement as the permutation approximation. Both rank score tests required weighting to maintain correct Type I errors when heterogeneity under the alternative model increased to 5 standard deviations across the domain of X. A double permutation procedure was developed to provide valid Type I errors for the permutation F-test when null models were forced through the origin. Power was similar for conditions where both T- and F-tests maintained correct Type I errors but the F-test provided some power at smaller n and extreme quantiles when the T-test had no power because of excessively conservative Type I errors. When the double permutation scheme was required for the permutation F-test to maintain valid Type I errors, power was less than for the T-test with decreasing sample size and increasing quantiles. Confidence intervals on parameters and tolerance intervals for future predictions were constructed based on test inversion for an example application relating trout densities to stream channel width:depth.

Nonparametric relevance-shifted multiple testing procedures for the analysis of high-dimensional multivariate data with small sample sizes.

PubMed

Frömke, Cornelia; Hothorn, Ludwig A; Kropf, Siegfried

2008-01-27

In many research areas it is necessary to find differences between treatment groups with several variables. For example, studies of microarray data seek to find a significant difference in location parameters from zero or one for ratios thereof for each variable. However, in some studies a significant deviation of the difference in locations from zero (or 1 in terms of the ratio) is biologically meaningless. A relevant difference or ratio is sought in such cases. This article addresses the use of relevance-shifted tests on ratios for a multivariate parallel two-sample group design. Two empirical procedures are proposed which embed the relevance-shifted test on ratios. As both procedures test a hypothesis for each variable, the resulting multiple testing problem has to be considered. Hence, the procedures include a multiplicity correction. Both procedures are extensions of available procedures for point null hypotheses achieving exact control of the familywise error rate. Whereas the shift of the null hypothesis alone would give straight-forward solutions, the problems that are the reason for the empirical considerations discussed here arise by the fact that the shift is considered in both directions and the whole parameter space in between these two limits has to be accepted as null hypothesis. The first algorithm to be discussed uses a permutation algorithm, and is appropriate for designs with a moderately large number of observations. However, many experiments have limited sample sizes. Then the second procedure might be more appropriate, where multiplicity is corrected according to a concept of data-driven order of hypotheses.

Decoding the Traumatic Memory among Women with PTSD: Implications for Neurocircuitry Models of PTSD and Real-Time fMRI Neurofeedback

PubMed Central

Cisler, Josh M.; Bush, Keith; James, G. Andrew; Smitherman, Sonet; Kilts, Clinton D.

2015-01-01

Posttraumatic Stress Disorder (PTSD) is characterized by intrusive recall of the traumatic memory. While numerous studies have investigated the neural processing mechanisms engaged during trauma memory recall in PTSD, these analyses have only focused on group-level contrasts that reveal little about the predictive validity of the identified brain regions. By contrast, a multivariate pattern analysis (MVPA) approach towards identifying the neural mechanisms engaged during trauma memory recall would entail testing whether a multivariate set of brain regions is reliably predictive of (i.e., discriminates) whether an individual is engaging in trauma or non-trauma memory recall. Here, we use a MVPA approach to test 1) whether trauma memory vs neutral memory recall can be predicted reliably using a multivariate set of brain regions among women with PTSD related to assaultive violence exposure (N=16), 2) the methodological parameters (e.g., spatial smoothing, number of memory recall repetitions, etc.) that optimize classification accuracy and reproducibility of the feature weight spatial maps, and 3) the correspondence between brain regions that discriminate trauma memory recall and the brain regions predicted by neurocircuitry models of PTSD. Cross-validation classification accuracy was significantly above chance for all methodological permutations tested; mean accuracy across participants was 76% for the methodological parameters selected as optimal for both efficiency and accuracy. Classification accuracy was significantly better for a voxel-wise approach relative to voxels within restricted regions-of-interest (ROIs); classification accuracy did not differ when using PTSD-related ROIs compared to randomly generated ROIs. ROI-based analyses suggested the reliable involvement of the left hippocampus in discriminating memory recall across participants and that the contribution of the left amygdala to the decision function was dependent upon PTSD symptom severity. These results have methodological implications for real-time fMRI neurofeedback of the trauma memory in PTSD and conceptual implications for neurocircuitry models of PTSD that attempt to explain core neural processing mechanisms mediating PTSD. PMID:26241958

Decoding the Traumatic Memory among Women with PTSD: Implications for Neurocircuitry Models of PTSD and Real-Time fMRI Neurofeedback.

PubMed

Cisler, Josh M; Bush, Keith; James, G Andrew; Smitherman, Sonet; Kilts, Clinton D

2015-01-01

Posttraumatic Stress Disorder (PTSD) is characterized by intrusive recall of the traumatic memory. While numerous studies have investigated the neural processing mechanisms engaged during trauma memory recall in PTSD, these analyses have only focused on group-level contrasts that reveal little about the predictive validity of the identified brain regions. By contrast, a multivariate pattern analysis (MVPA) approach towards identifying the neural mechanisms engaged during trauma memory recall would entail testing whether a multivariate set of brain regions is reliably predictive of (i.e., discriminates) whether an individual is engaging in trauma or non-trauma memory recall. Here, we use a MVPA approach to test 1) whether trauma memory vs neutral memory recall can be predicted reliably using a multivariate set of brain regions among women with PTSD related to assaultive violence exposure (N=16), 2) the methodological parameters (e.g., spatial smoothing, number of memory recall repetitions, etc.) that optimize classification accuracy and reproducibility of the feature weight spatial maps, and 3) the correspondence between brain regions that discriminate trauma memory recall and the brain regions predicted by neurocircuitry models of PTSD. Cross-validation classification accuracy was significantly above chance for all methodological permutations tested; mean accuracy across participants was 76% for the methodological parameters selected as optimal for both efficiency and accuracy. Classification accuracy was significantly better for a voxel-wise approach relative to voxels within restricted regions-of-interest (ROIs); classification accuracy did not differ when using PTSD-related ROIs compared to randomly generated ROIs. ROI-based analyses suggested the reliable involvement of the left hippocampus in discriminating memory recall across participants and that the contribution of the left amygdala to the decision function was dependent upon PTSD symptom severity. These results have methodological implications for real-time fMRI neurofeedback of the trauma memory in PTSD and conceptual implications for neurocircuitry models of PTSD that attempt to explain core neural processing mechanisms mediating PTSD.

An analog scrambler for speech based on sequential permutations in time and frequency

NASA Astrophysics Data System (ADS)

Cox, R. V.; Jayant, N. S.; McDermott, B. J.

Permutation of speech segments is an operation that is frequently used in the design of scramblers for analog speech privacy. In this paper, a sequential procedure for segment permutation is considered. This procedure can be extended to two dimensional permutation of time segments and frequency bands. By subjective testing it is shown that this combination gives a residual intelligibility for spoken digits of 20 percent with a delay of 256 ms. (A lower bound for this test would be 10 percent). The complexity of implementing such a system is considered and the issues of synchronization and channel equalization are addressed. The computer simulation results for the system using both real and simulated channels are examined.

A 1.375-approximation algorithm for sorting by transpositions.

PubMed

Elias, Isaac; Hartman, Tzvika

2006-01-01

Sorting permutations by transpositions is an important problem in genome rearrangements. A transposition is a rearrangement operation in which a segment is cut out of the permutation and pasted in a different location. The complexity of this problem is still open and it has been a 10-year-old open problem to improve the best known 1.5-approximation algorithm. In this paper, we provide a 1.375-approximation algorithm for sorting by transpositions. The algorithm is based on a new upper bound on the diameter of 3-permutations. In addition, we present some new results regarding the transposition diameter: we improve the lower bound for the transposition diameter of the symmetric group and determine the exact transposition diameter of simple permutations.

Permutational distribution of the log-rank statistic under random censorship with applications to carcinogenicity assays.

PubMed

Heimann, G; Neuhaus, G

1998-03-01

In the random censorship model, the log-rank test is often used for comparing a control group with different dose groups. If the number of tumors is small, so-called exact methods are often applied for computing critical values from a permutational distribution. Two of these exact methods are discussed and shown to be incorrect. The correct permutational distribution is derived and studied with respect to its behavior under unequal censoring in the light of recent results proving that the permutational version and the unconditional version of the log-rank test are asymptotically equivalent even under unequal censoring. The log-rank test is studied by simulations of a realistic scenario from a bioassay with small numbers of tumors.

Accurate and fast multiple-testing correction in eQTL studies.

PubMed

Sul, Jae Hoon; Raj, Towfique; de Jong, Simone; de Bakker, Paul I W; Raychaudhuri, Soumya; Ophoff, Roel A; Stranger, Barbara E; Eskin, Eleazar; Han, Buhm

2015-06-04

In studies of expression quantitative trait loci (eQTLs), it is of increasing interest to identify eGenes, the genes whose expression levels are associated with variation at a particular genetic variant. Detecting eGenes is important for follow-up analyses and prioritization because genes are the main entities in biological processes. To detect eGenes, one typically focuses on the genetic variant with the minimum p value among all variants in cis with a gene and corrects for multiple testing to obtain a gene-level p value. For performing multiple-testing correction, a permutation test is widely used. Because of growing sample sizes of eQTL studies, however, the permutation test has become a computational bottleneck in eQTL studies. In this paper, we propose an efficient approach for correcting for multiple testing and assess eGene p values by utilizing a multivariate normal distribution. Our approach properly takes into account the linkage-disequilibrium structure among variants, and its time complexity is independent of sample size. By applying our small-sample correction techniques, our method achieves high accuracy in both small and large studies. We have shown that our method consistently produces extremely accurate p values (accuracy > 98%) for three human eQTL datasets with different sample sizes and SNP densities: the Genotype-Tissue Expression pilot dataset, the multi-region brain dataset, and the HapMap 3 dataset. Copyright © 2015 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Security Analysis of Some Diffusion Mechanisms Used in Chaotic Ciphers

NASA Astrophysics Data System (ADS)

Zhang, Leo Yu; Zhang, Yushu; Liu, Yuansheng; Yang, Anjia; Chen, Guanrong

As a variant of the substitution-permutation network, the permutation-diffusion structure has received extensive attention in the field of chaotic cryptography over the last three decades. Because of the high implementation speed and nonlinearity over GF(2), the Galois field of two elements, mixing modulo addition/multiplication and Exclusive OR becomes very popular in various designs to achieve the desired diffusion effect. This paper reports that some diffusion mechanisms based on modulo addition/multiplication and Exclusive OR are not resistant to plaintext attacks as claimed. By cracking several recently proposed chaotic ciphers as examples, it is demonstrated that a good understanding of the strength and weakness of these crypto-primitives is crucial for designing more practical chaotic encryption algorithms in the future.

Assessing the potential for raw meat to influence human colonization with Staphylococcus aureus.

PubMed

Carrel, Margaret; Zhao, Chang; Thapaliya, Dipendra; Bitterman, Patrick; Kates, Ashley E; Hanson, Blake M; Smith, Tara C

2017-09-07

The role of household meat handling and consumption in the transfer of Staphylococcus aureus (S. aureus) from livestock to consumers is not well understood. Examining the similarity of S. aureus colonizing humans and S. aureus in meat from the stores in which those individuals shop can provide insight into the role of meat in human S. aureus colonization. S. aureus isolates were collected from individuals in rural and urban communities in Iowa (n = 3347) and contemporaneously from meat products in stores where participants report purchasing meat (n = 913). The staphylococcal protein A (spa) gene was sequenced for all isolates to determine a spa type. Morisita indices and Permutational Multivariate Analysis of Variance Using Distance Matrices (PERMANOVA) were used to determine the relationship between spa type composition among human samples and meat samples. spa type composition was significantly different between households and meat sampled from their associated grocery stores. spa types found in meat were not significantly different regardless of the store or county in which they were sampled. spa types in people also exhibit high similarity regardless of residential location in urban or rural counties. Such findings suggest meat is not an important source of S. aureus colonization in shoppers.

The placenta harbors a unique microbiome.

PubMed

Aagaard, Kjersti; Ma, Jun; Antony, Kathleen M; Ganu, Radhika; Petrosino, Joseph; Versalovic, James

2014-05-21

Humans and their microbiomes have coevolved as a physiologic community composed of distinct body site niches with metabolic and antigenic diversity. The placental microbiome has not been robustly interrogated, despite recent demonstrations of intracellular bacteria with diverse metabolic and immune regulatory functions. A population-based cohort of placental specimens collected under sterile conditions from 320 subjects with extensive clinical data was established for comparative 16S ribosomal DNA-based and whole-genome shotgun (WGS) metagenomic studies. Identified taxa and their gene carriage patterns were compared to other human body site niches, including the oral, skin, airway (nasal), vaginal, and gut microbiomes from nonpregnant controls. We characterized a unique placental microbiome niche, composed of nonpathogenic commensal microbiota from the Firmicutes, Tenericutes, Proteobacteria, Bacteroidetes, and Fusobacteria phyla. In aggregate, the placental microbiome profiles were most akin (Bray-Curtis dissimilarity <0.3) to the human oral microbiome. 16S-based operational taxonomic unit analyses revealed associations of the placental microbiome with a remote history of antenatal infection (permutational multivariate analysis of variance, P = 0.006), such as urinary tract infection in the first trimester, as well as with preterm birth <37 weeks (P = 0.001). Copyright © 2014, American Association for the Advancement of Science.

Estimation of absolute solvent and solvation shell entropies via permutation reduction

NASA Astrophysics Data System (ADS)

Reinhard, Friedemann; Grubmüller, Helmut

2007-01-01

Despite its prominent contribution to the free energy of solvated macromolecules such as proteins or DNA, and although principally contained within molecular dynamics simulations, the entropy of the solvation shell is inaccessible to straightforward application of established entropy estimation methods. The complication is twofold. First, the configurational space density of such systems is too complex for a sufficiently accurate fit. Second, and in contrast to the internal macromolecular dynamics, the configurational space volume explored by the diffusive motion of the solvent molecules is too large to be exhaustively sampled by current simulation techniques. Here, we develop a method to overcome the second problem and to significantly alleviate the first one. We propose to exploit the permutation symmetry of the solvent by transforming the trajectory in a way that renders established estimation methods applicable, such as the quasiharmonic approximation or principal component analysis. Our permutation-reduced approach involves a combinatorial problem, which is solved through its equivalence with the linear assignment problem, for which O(N3) methods exist. From test simulations of dense Lennard-Jones gases, enhanced convergence and improved entropy estimates are obtained. Moreover, our approach renders diffusive systems accessible to improved fit functions.

Analysis of crude oil markets with improved multiscale weighted permutation entropy

NASA Astrophysics Data System (ADS)

Niu, Hongli; Wang, Jun; Liu, Cheng

2018-03-01

Entropy measures are recently extensively used to study the complexity property in nonlinear systems. Weighted permutation entropy (WPE) can overcome the ignorance of the amplitude information of time series compared with PE and shows a distinctive ability to extract complexity information from data having abrupt changes in magnitude. Improved (or sometimes called composite) multi-scale (MS) method possesses the advantage of reducing errors and improving the accuracy when applied to evaluate multiscale entropy values of not enough long time series. In this paper, we combine the merits of WPE and improved MS to propose the improved multiscale weighted permutation entropy (IMWPE) method for complexity investigation of a time series. Then it is validated effective through artificial data: white noise and 1 / f noise, and real market data of Brent and Daqing crude oil. Meanwhile, the complexity properties of crude oil markets are explored respectively of return series, volatility series with multiple exponents and EEMD-produced intrinsic mode functions (IMFs) which represent different frequency components of return series. Moreover, the instantaneous amplitude and frequency of Brent and Daqing crude oil are analyzed by the Hilbert transform utilized to each IMF.

cit: hypothesis testing software for mediation analysis in genomic applications.

PubMed

Millstein, Joshua; Chen, Gary K; Breton, Carrie V

2016-08-01

The challenges of successfully applying causal inference methods include: (i) satisfying underlying assumptions, (ii) limitations in data/models accommodated by the software and (iii) low power of common multiple testing approaches. The causal inference test (CIT) is based on hypothesis testing rather than estimation, allowing the testable assumptions to be evaluated in the determination of statistical significance. A user-friendly software package provides P-values and optionally permutation-based FDR estimates (q-values) for potential mediators. It can handle single and multiple binary and continuous instrumental variables, binary or continuous outcome variables and adjustment covariates. Also, the permutation-based FDR option provides a non-parametric implementation. Simulation studies demonstrate the validity of the cit package and show a substantial advantage of permutation-based FDR over other common multiple testing strategies. The cit open-source R package is freely available from the CRAN website (https://cran.r-project.org/web/packages/cit/index.html) with embedded C ++ code that utilizes the GNU Scientific Library, also freely available (http://www.gnu.org/software/gsl/). joshua.millstein@usc.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Error-free holographic frames encryption with CA pixel-permutation encoding algorithm

NASA Astrophysics Data System (ADS)

Li, Xiaowei; Xiao, Dan; Wang, Qiong-Hua

2018-01-01

The security of video data is necessary in network security transmission hence cryptography is technique to make video data secure and unreadable to unauthorized users. In this paper, we propose a holographic frames encryption technique based on the cellular automata (CA) pixel-permutation encoding algorithm. The concise pixel-permutation algorithm is used to address the drawbacks of the traditional CA encoding methods. The effectiveness of the proposed video encoding method is demonstrated by simulation examples.

Photographs and Committees: Activities That Help Students Discover Permutations and Combinations.

ERIC Educational Resources Information Center

Szydlik, Jennifer Earles

2000-01-01

Presents problem situations that support students when discovering the multiplication principle, permutations, combinations, Pascal's triangle, and relationships among those objects in a concrete context. (ASK)

A permutation characterization of Sturm global attractors of Hamiltonian type

NASA Astrophysics Data System (ADS)

Fiedler, Bernold; Rocha, Carlos; Wolfrum, Matthias

We consider Neumann boundary value problems of the form u=u+f on the interval 0⩽x⩽π for dissipative nonlinearities f=f(u). A permutation characterization for the global attractors of the semiflows generated by these equations is well known, even in the much more general case f=f(x,u,u). We present a permutation characterization for the global attractors in the restrictive class of nonlinearities f=f(u). In this class the stationary solutions of the parabolic equation satisfy the second order ODE v+f(v)=0 and we obtain the permutation characterization from a characterization of the set of 2 π-periodic orbits of this planar Hamiltonian system. Our results are based on a diligent discussion of this mere pendulum equation.

PBOOST: a GPU-based tool for parallel permutation tests in genome-wide association studies.

PubMed

Yang, Guangyuan; Jiang, Wei; Yang, Qiang; Yu, Weichuan

2015-05-01

The importance of testing associations allowing for interactions has been demonstrated by Marchini et al. (2005). A fast method detecting associations allowing for interactions has been proposed by Wan et al. (2010a). The method is based on likelihood ratio test with the assumption that the statistic follows the χ(2) distribution. Many single nucleotide polymorphism (SNP) pairs with significant associations allowing for interactions have been detected using their method. However, the assumption of χ(2) test requires the expected values in each cell of the contingency table to be at least five. This assumption is violated in some identified SNP pairs. In this case, likelihood ratio test may not be applicable any more. Permutation test is an ideal approach to checking the P-values calculated in likelihood ratio test because of its non-parametric nature. The P-values of SNP pairs having significant associations with disease are always extremely small. Thus, we need a huge number of permutations to achieve correspondingly high resolution for the P-values. In order to investigate whether the P-values from likelihood ratio tests are reliable, a fast permutation tool to accomplish large number of permutations is desirable. We developed a permutation tool named PBOOST. It is based on GPU with highly reliable P-value estimation. By using simulation data, we found that the P-values from likelihood ratio tests will have relative error of >100% when 50% cells in the contingency table have expected count less than five or when there is zero expected count in any of the contingency table cells. In terms of speed, PBOOST completed 10(7) permutations for a single SNP pair from the Wellcome Trust Case Control Consortium (WTCCC) genome data (Wellcome Trust Case Control Consortium, 2007) within 1 min on a single Nvidia Tesla M2090 device, while it took 60 min in a single CPU Intel Xeon E5-2650 to finish the same task. More importantly, when simultaneously testing 256 SNP pairs for 10(7) permutations, our tool took only 5 min, while the CPU program took 10 h. By permuting on a GPU cluster consisting of 40 nodes, we completed 10(12) permutations for all 280 SNP pairs reported with P-values smaller than 1.6 × 10⁻¹² in the WTCCC datasets in 1 week. The source code and sample data are available at http://bioinformatics.ust.hk/PBOOST.zip. gyang@ust.hk; eeyu@ust.hk Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Engineering calculations for solving the orbital allotment problem

NASA Technical Reports Server (NTRS)

Reilly, C.; Walton, E. K.; Mount-Campbell, C.; Caldecott, R.; Aebker, E.; Mata, F.

1988-01-01

Four approaches for calculating downlink interferences for shaped-beam antennas are described. An investigation of alternative mixed-integer programming models for satellite synthesis is summarized. Plans for coordinating the various programs developed under this grant are outlined. Two procedures for ordering satellites to initialize the k-permutation algorithm are proposed. Results are presented for the k-permutation algorithms. Feasible solutions are found for 5 of the 6 problems considered. Finally, it is demonstrated that the k-permutation algorithm can be used to solve arc allotment problems.

INTERMITTENT AND PERENNIAL STREAM MACROINVERTEBRATE COMMUNITY RESPONSE TO IMPERVIOUS COVER: THRESHOLD INDICATOR TAXA ANALYSIS AND PERMUTATIONS

EPA Science Inventory

The urban stream syndrome and the impact of impervious cover on macroinvertebrate communities is well-documented, but many exclude intermittent streams despite their prevalence. This study investigated macroinvertebrate communities of intermittent and perennial streams separately...

Molecular characterization of endocarditis-associated Staphylococcus aureus.

PubMed

Nethercott, Cara; Mabbett, Amanda N; Totsika, Makrina; Peters, Paul; Ortiz, Juan C; Nimmo, Graeme R; Coombs, Geoffrey W; Walker, Mark J; Schembri, Mark A

2013-07-01

Infective endocarditis (IE) is a life-threatening infection of the heart endothelium and valves. Staphylococcus aureus is a predominant cause of severe IE and is frequently associated with infections in health care settings and device-related infections. Multilocus sequence typing (MLST), spa typing, and virulence gene microarrays are frequently used to classify S. aureus clinical isolates. This study examined the utility of these typing tools to investigate S. aureus epidemiology associated with IE. Ninety-seven S. aureus isolates were collected from patients diagnosed with (i) IE, (ii) bloodstream infection related to medical devices, (iii) bloodstream infection not related to medical devices, and (iv) skin or soft-tissue infections. The MLST clonal complex (CC) for each isolate was determined and compared to the CCs of members of the S. aureus population by eBURST analysis. The spa type of all isolates was also determined. A null model was used to determine correlations of IE with CC and spa type. DNA microarray analysis was performed, and a permutational analysis of multivariate variance (PERMANOVA) and principal coordinates analysis were conducted to identify genotypic differences between IE and non-IE strains. CC12, CC20, and spa type t160 were significantly associated with IE S. aureus. A subset of virulence-associated genes and alleles, including genes encoding staphylococcal superantigen-like proteins, fibrinogen-binding protein, and a leukocidin subunit, also significantly correlated with IE isolates. MLST, spa typing, and microarray analysis are promising tools for monitoring S. aureus epidemiology associated with IE. Further research to determine a role for the S. aureus IE-associated virulence genes identified in this study is warranted.

Molecular Characterization of Endocarditis-Associated Staphylococcus aureus

PubMed Central

Nethercott, Cara; Mabbett, Amanda N.; Totsika, Makrina; Peters, Paul; Ortiz, Juan C.; Nimmo, Graeme R.; Coombs, Geoffrey W.

2013-01-01

Infective endocarditis (IE) is a life-threatening infection of the heart endothelium and valves. Staphylococcus aureus is a predominant cause of severe IE and is frequently associated with infections in health care settings and device-related infections. Multilocus sequence typing (MLST), spa typing, and virulence gene microarrays are frequently used to classify S. aureus clinical isolates. This study examined the utility of these typing tools to investigate S. aureus epidemiology associated with IE. Ninety-seven S. aureus isolates were collected from patients diagnosed with (i) IE, (ii) bloodstream infection related to medical devices, (iii) bloodstream infection not related to medical devices, and (iv) skin or soft-tissue infections. The MLST clonal complex (CC) for each isolate was determined and compared to the CCs of members of the S. aureus population by eBURST analysis. The spa type of all isolates was also determined. A null model was used to determine correlations of IE with CC and spa type. DNA microarray analysis was performed, and a permutational analysis of multivariate variance (PERMANOVA) and principal coordinates analysis were conducted to identify genotypic differences between IE and non-IE strains. CC12, CC20, and spa type t160 were significantly associated with IE S. aureus. A subset of virulence-associated genes and alleles, including genes encoding staphylococcal superantigen-like proteins, fibrinogen-binding protein, and a leukocidin subunit, also significantly correlated with IE isolates. MLST, spa typing, and microarray analysis are promising tools for monitoring S. aureus epidemiology associated with IE. Further research to determine a role for the S. aureus IE-associated virulence genes identified in this study is warranted. PMID:23616460

Responses of Bacterial Communities in Arable Soils in a Rice-Wheat Cropping System to Different Fertilizer Regimes and Sampling Times

PubMed Central

Zhao, Jun; Ni, Tian; Li, Yong; Xiong, Wu; Ran, Wei; Shen, Biao; Shen, Qirong; Zhang, Ruifu

2014-01-01

Soil physicochemical properties, soil microbial biomass and bacterial community structures in a rice-wheat cropping system subjected to different fertilizer regimes were investigated in two seasons (June and October). All fertilizer regimes increased the soil microbial biomass carbon and nitrogen. Both fertilizer regime and time had a significant effect on soil physicochemical properties and bacterial community structure. The combined application of inorganic fertilizer and manure organic-inorganic fertilizer significantly enhanced the bacterial diversity in both seasons. The bacterial communities across all samples were dominated by Proteobacteria, Acidobacteria and Chloroflexi at the phylum level. Permutational multivariate analysis confirmed that both fertilizer treatment and season were significant factors in the variation of the composition of the bacterial community. Hierarchical cluster analysis based on Bray-Curtis distances further revealed that bacterial communities were separated primarily by season. The effect of fertilizer treatment is significant (P = 0.005) and accounts for 7.43% of the total variation in bacterial community. Soil nutrients (e.g., available K, total N, total P and organic matter) rather than pH showed significant correlation with the majority of abundant taxa. In conclusion, both fertilizer treatment and seasonal changes affect soil properties, microbial biomass and bacterial community structure. The application of NPK plus manure organic-inorganic fertilizer may be a sound fertilizer practice for sustainable food production. PMID:24465530

Intraspecies variation in a widely distributed tree species regulates the responses of soil microbiome to different temperature regimes.

PubMed

Zhang, Cui-Jing; Delgado-Baquerizo, Manuel; Drake, John E; Reich, Peter B; Tjoelker, Mark G; Tissue, David T; Wang, Jun-Tao; He, Ji-Zheng; Singh, Brajesh K

2018-04-01

Plant characteristics in different provenances within a single species may vary in response to climate change, which might alter soil microbial communities and ecosystem functions. We conducted a glasshouse experiment and grew seedlings of three provenances (temperate, subtropical and tropical origins) of a tree species (i.e., Eucalyptus tereticornis) at different growth temperatures (18, 21.5, 25, 28.5, 32 and 35.5°C) for 54 days. At the end of the experiment, bacterial and fungal community composition, diversity and abundance were characterized. Measured soil functions included surrogates of microbial respiration, enzyme activities and nutrient cycling. Using Permutation multivariate analysis of variance (PerMANOVA) and network analysis, we found that the identity of tree provenances regulated both structure and function of soil microbiomes. In some cases, tree provenances substantially affected the response of microbial communities to the temperature treatments. For example, we found significant interactions of temperature and tree provenance on bacterial community and relative abundances of Chloroflexi and Zygomycota, and inorganic nitrogen. Microbial abundance was altered in response to increasing temperature, but was not affected by tree provenances. Our study provides novel evidence that even a small variation in biotic components (i.e., intraspecies tree variation) can significantly influence the response of soil microbial community composition and specific soil functions to global warming. © 2018 Society for Applied Microbiology and John Wiley & Sons Ltd.

Under which climate and soil conditions the plant productivity-precipitation relationship is linear or nonlinear?

PubMed

Ye, Jian-Sheng; Pei, Jiu-Ying; Fang, Chao

2018-03-01

Understanding under which climate and soil conditions the plant productivity-precipitation relationship is linear or nonlinear is useful for accurately predicting the response of ecosystem function to global environmental change. Using long-term (2000-2016) net primary productivity (NPP)-precipitation datasets derived from satellite observations, we identify >5600pixels in the North Hemisphere landmass that fit either linear or nonlinear temporal NPP-precipitation relationships. Differences in climate (precipitation, radiation, ratio of actual to potential evapotranspiration, temperature) and soil factors (nitrogen, phosphorous, organic carbon, field capacity) between the linear and nonlinear types are evaluated. Our analysis shows that both linear and nonlinear types exhibit similar interannual precipitation variabilities and occurrences of extreme precipitation. Permutational multivariate analysis of variance suggests that linear and nonlinear types differ significantly regarding to radiation, ratio of actual to potential evapotranspiration, and soil factors. The nonlinear type possesses lower radiation and/or less soil nutrients than the linear type, thereby suggesting that nonlinear type features higher degree of limitation from resources other than precipitation. This study suggests several factors limiting the responses of plant productivity to changes in precipitation, thus causing nonlinear NPP-precipitation pattern. Precipitation manipulation and modeling experiments should combine with changes in other climate and soil factors to better predict the response of plant productivity under future climate. Copyright © 2017 Elsevier B.V. All rights reserved.

Population characteristics of DNA fingerprints in humpback whales (Megaptera novaeangliae).

PubMed

Baker, C S; Gilbert, D A; Weinrich, M T; Lambertsen, R; Calambokidis, J; McArdle, B; Chambers, G K; O'Brien, S J

1993-01-01

Humpback whales exhibit a remarkable social organization that is characterized by seasonal long-distance migration (> 10,000 km/year) between summer feeding grounds in high latitudes and winter calving and breeding grounds in tropical or near-tropical waters. All populations are currently considered endangered as a result of intensive commercial exploitation during the last 200 years. Using three hypervariable minisatellite DNA probes (33.15, 3'HVR, and M13) originally developed for studies of human genetic variation, we examined genetic variation within and among three regional subpopulations of humpback whales from the North Pacific and one from the North Atlantic oceans. Analysis of DNA extracted from skin tissues collected by biopsy darting from free-ranging whales revealed considerable variation in each subpopulation. The extent of this variation argues against a recent history of inbreeding among humpback whales as a result of nineteenth- and twentieth-century hunting. A canonical variate analysis suggested a relationship between scaled genetic distance, based on similarities of DNA fingerprints, and geographic distance (i.e., longitude of regional subpopulation). Significant categorical differences were found between the two oceanic populations using a multivariate analysis of variance (MANOVA) with a modification of the Mantel nonparametric permutation test. The relationship between DNA fingerprint similarities and geographic distance suggests that nuclear gene flow between regional subpopulations within the North Pacific is restricted by relatively low rates of migratory interchange between breeding grounds or assortative mating on common wintering grounds.

Permutation invariant polynomial neural network approach to fitting potential energy surfaces. II. Four-atom systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Jun; Jiang, Bin; Guo, Hua, E-mail: hguo@unm.edu

2013-11-28

A rigorous, general, and simple method to fit global and permutation invariant potential energy surfaces (PESs) using neural networks (NNs) is discussed. This so-called permutation invariant polynomial neural network (PIP-NN) method imposes permutation symmetry by using in its input a set of symmetry functions based on PIPs. For systems with more than three atoms, it is shown that the number of symmetry functions in the input vector needs to be larger than the number of internal coordinates in order to include both the primary and secondary invariant polynomials. This PIP-NN method is successfully demonstrated in three atom-triatomic reactive systems, resultingmore » in full-dimensional global PESs with average errors on the order of meV. These PESs are used in full-dimensional quantum dynamical calculations.« less

Permutation entropy analysis of financial time series based on Hill's diversity number

NASA Astrophysics Data System (ADS)

Zhang, Yali; Shang, Pengjian

2017-12-01

In this paper the permutation entropy based on Hill's diversity number (Nn,r) is introduced as a new way to assess the complexity of a complex dynamical system such as stock market. We test the performance of this method with simulated data. Results show that Nn,r with appropriate parameters is more sensitive to the change of system and describes the trends of complex systems clearly. In addition, we research the stock closing price series from different data that consist of six indices: three US stock indices and three Chinese stock indices during different periods, Nn,r can quantify the changes of complexity for stock market data. Moreover, we get richer information from Nn,r, and obtain some properties about the differences between the US and Chinese stock indices.

Adinkra (in)equivalence from Coxeter group representations: A case study

NASA Astrophysics Data System (ADS)

Chappell, Isaac; Gates, S. James; Hübsch, T.

2014-02-01

Using a MathematicaTM code, we present a straightforward numerical analysis of the 384-dimensional solution space of signed permutation 4×4 matrices, which in sets of four, provide representations of the 𝒢ℛ(4, 4) algebra, closely related to the 𝒩 = 1 (simple) supersymmetry algebra in four-dimensional space-time. Following after ideas discussed in previous papers about automorphisms and classification of adinkras and corresponding supermultiplets, we make a new and alternative proposal to use equivalence classes of the (unsigned) permutation group S4 to define distinct representations of higher-dimensional spin bundles within the context of adinkras. For this purpose, the definition of a dual operator akin to the well-known Hodge star is found to partition the space of these 𝒢ℛ(4, 4) representations into three suggestive classes.

Quantile-based permutation thresholds for quantitative trait loci hotspots.

PubMed

Neto, Elias Chaibub; Keller, Mark P; Broman, Andrew F; Attie, Alan D; Jansen, Ritsert C; Broman, Karl W; Yandell, Brian S

2012-08-01

Quantitative trait loci (QTL) hotspots (genomic locations affecting many traits) are a common feature in genetical genomics studies and are biologically interesting since they may harbor critical regulators. Therefore, statistical procedures to assess the significance of hotspots are of key importance. One approach, randomly allocating observed QTL across the genomic locations separately by trait, implicitly assumes all traits are uncorrelated. Recently, an empirical test for QTL hotspots was proposed on the basis of the number of traits that exceed a predetermined LOD value, such as the standard permutation LOD threshold. The permutation null distribution of the maximum number of traits across all genomic locations preserves the correlation structure among the phenotypes, avoiding the detection of spurious hotspots due to nongenetic correlation induced by uncontrolled environmental factors and unmeasured variables. However, by considering only the number of traits above a threshold, without accounting for the magnitude of the LOD scores, relevant information is lost. In particular, biologically interesting hotspots composed of a moderate to small number of traits with strong LOD scores may be neglected as nonsignificant. In this article we propose a quantile-based permutation approach that simultaneously accounts for the number and the LOD scores of traits within the hotspots. By considering a sliding scale of mapping thresholds, our method can assess the statistical significance of both small and large hotspots. Although the proposed approach can be applied to any type of heritable high-volume "omic" data set, we restrict our attention to expression (e)QTL analysis. We assess and compare the performances of these three methods in simulations and we illustrate how our approach can effectively assess the significance of moderate and small hotspots with strong LOD scores in a yeast expression data set.

Four-point functions and the permutation group S4

NASA Astrophysics Data System (ADS)

Eichmann, Gernot; Fischer, Christian S.; Heupel, Walter

2015-09-01

Four-point functions are at the heart of many interesting physical processes. A prime example is the light-by-light scattering amplitude, which plays an important role in the calculation of hadronic contributions to the anomalous magnetic moment of the muon. In the calculation of such quantities one faces the challenge of finding a suitable and well-behaved basis of tensor structures in coordinate and/or momentum space. Provided all (or many) of the external legs represent similar particle content, a powerful tool to construct and organize such bases is the permutation group S4. We introduce an efficient notation for dealing with the irreducible multiplets of S4, and we highlight the merits of this treatment by exemplifying four-point functions with gauge-boson legs such as the four-gluon vertex and the light-by-light scattering amplitude. The multiplet analysis is also useful for isolating the important kinematic regions and the dynamical singularity content of such amplitudes. Our analysis serves as a basis for future efficient calculations of these and similar objects.

Permutation entropy of fractional Brownian motion and fractional Gaussian noise

NASA Astrophysics Data System (ADS)

Zunino, L.; Pérez, D. G.; Martín, M. T.; Garavaglia, M.; Plastino, A.; Rosso, O. A.

2008-06-01

We have worked out theoretical curves for the permutation entropy of the fractional Brownian motion and fractional Gaussian noise by using the Bandt and Shiha [C. Bandt, F. Shiha, J. Time Ser. Anal. 28 (2007) 646] theoretical predictions for their corresponding relative frequencies. Comparisons with numerical simulations show an excellent agreement. Furthermore, the entropy-gap in the transition between these processes, observed previously via numerical results, has been here theoretically validated. Also, we have analyzed the behaviour of the permutation entropy of the fractional Gaussian noise for different time delays.

An Analysis of Document Category Prediction Responses to Classifier Model Parameter Treatment Permutations within the Software Design Patterns Subject Domain

ERIC Educational Resources Information Center

Pankau, Brian L.

2009-01-01

This empirical study evaluates the document category prediction effectiveness of Naive Bayes (NB) and K-Nearest Neighbor (KNN) classifier treatments built from different feature selection and machine learning settings and trained and tested against textual corpora of 2300 Gang-Of-Four (GOF) design pattern documents. Analysis of the experiment's…

An EEMD-ICA Approach to Enhancing Artifact Rejection for Noisy Multivariate Neural Data.

PubMed

Zeng, Ke; Chen, Dan; Ouyang, Gaoxiang; Wang, Lizhe; Liu, Xianzeng; Li, Xiaoli

2016-06-01

As neural data are generally noisy, artifact rejection is crucial for data preprocessing. It has long been a grand research challenge for an approach which is able: 1) to remove the artifacts and 2) to avoid loss or disruption of the structural information at the same time, thus the risk of introducing bias to data interpretation may be minimized. In this study, an approach (namely EEMD-ICA) was proposed to first decompose multivariate neural data that are possibly noisy into intrinsic mode functions (IMFs) using ensemble empirical mode decomposition (EEMD). Independent component analysis (ICA) was then applied to the IMFs to separate the artifactual components. The approach was tested against the classical ICA and the automatic wavelet ICA (AWICA) methods, which were dominant methods for artifact rejection. In order to evaluate the effectiveness of the proposed approach in handling neural data possibly with intensive noises, experiments on artifact removal were performed using semi-simulated data mixed with a variety of noises. Experimental results indicate that the proposed approach continuously outperforms the counterparts in terms of both normalized mean square error (NMSE) and Structure SIMilarity (SSIM). The superiority becomes even greater with the decrease of SNR in all cases, e.g., SSIM of the EEMD-ICA can almost double that of AWICA and triple that of ICA. To further examine the potentials of the approach in sophisticated applications, the approach together with the counterparts were used to preprocess a real-life epileptic EEG with absence seizure. Experiments were carried out with the focus on characterizing the dynamics of the data after artifact rejection, i.e., distinguishing seizure-free, pre-seizure and seizure states. Using multi-scale permutation entropy to extract feature and linear discriminant analysis for classification, the EEMD-ICA performed the best for classifying the states (87.4%, about 4.1% and 8.7% higher than that of AWICA and ICA respectively), which was closest to the results of the manually selected dataset (89.7%).

Relationships between depressive symptoms and self-reported unintentional injuries: the cross-sectional population–based FIN-D2D survey

PubMed Central

2012-01-01

Background There is a lack of knowledge on the influence of different levels of physical activity (PA) on unintentional injuries among those with depressive symptoms (DS). The aim of this study was to evaluate the relationship between PA categories and unintentional injuries among participants with and without DS based on a cross-sectional population–based FIN-D2D survey conducted in 2007. Methods Out of 4500, 2682 participants (60%) aged 45–74 years attended in this study. The unintentional injuries over the past year were captured in a questionnaire. DS were determined with the Beck Depression Inventory (≥ 10 points) and PA with the International Physical Activity Questionnaire. The statistical significance between DS and unintentional injury categories was evaluated by using t-test, chi-square test, or permutation test, analysis of covariance, or regression models. The factors related to unintentional injuries were estimated by univariate and multivariate logistic regression models. Results The proportion of subjects with unintentional injuries was higher among those with DS (17%) compared to those without DS (10%) (age- and gender-adjusted p = 0.023). The median (range) number of activity-loss days after injury was 22 (0–365) in participants with DS and 7 (0–120) in participants without DS ( p = 0.009). The percentage of subjects with unintentional injuries was not significantly different between PA categories in participants with DS and without DS. A stepwise multivariate logistic regression analysis showed that DS, functional ability, and musculoskeletal diseases were related to unintentional injuries. Conclusions PA level was not related to unintentional injuries, whereas those with DS had a higher prevalence of unintentional injuries and prolonged activity-loss after injury. These results underline the importance of injury prevention, especially among those who have DS and additional risk factors. PMID:22781103

Randomization Procedures Applied to Analysis of Ballistic Data

DTIC Science & Technology

1991-06-01

test,;;15. NUMBER OF PAGES data analysis; computationally intensive statistics ; randomization tests; permutation tests; 16 nonparametric statistics ...be 0.13. 8 Any reasonable statistical procedure would fail to support the notion of improvement of dynamic over standard indexing based on this data ...AD-A238 389 TECHNICAL REPORT BRL-TR-3245 iBRL RANDOMIZATION PROCEDURES APPLIED TO ANALYSIS OF BALLISTIC DATA MALCOLM S. TAYLOR BARRY A. BODT - JUNE

A simplified formalism of the algebra of partially transposed permutation operators with applications

NASA Astrophysics Data System (ADS)

Mozrzymas, Marek; Studziński, Michał; Horodecki, Michał

2018-03-01

Herein we continue the study of the representation theory of the algebra of permutation operators acting on the n -fold tensor product space, partially transposed on the last subsystem. We develop the concept of partially reduced irreducible representations, which allows us to significantly simplify previously proved theorems and, most importantly, derive new results for irreducible representations of the mentioned algebra. In our analysis we are able to reduce the complexity of the central expressions by getting rid of sums over all permutations from the symmetric group, obtaining equations which are much more handy in practical applications. We also find relatively simple matrix representations for the generators of the underlying algebra. The obtained simplifications and developments are applied to derive the characteristics of a deterministic port-based teleportation scheme written purely in terms of irreducible representations of the studied algebra. We solve an eigenproblem for the generators of the algebra, which is the first step towards a hybrid port-based teleportation scheme and gives us new proofs of the asymptotic behaviour of teleportation fidelity. We also show a connection between the density operator characterising port-based teleportation and a particular matrix composed of an irreducible representation of the symmetric group, which encodes properties of the investigated algebra.

Permutation auto-mutual information of electroencephalogram in anesthesia

NASA Astrophysics Data System (ADS)

Liang, Zhenhu; Wang, Yinghua; Ouyang, Gaoxiang; Voss, Logan J.; Sleigh, Jamie W.; Li, Xiaoli

2013-04-01

Objective. The dynamic change of brain activity in anesthesia is an interesting topic for clinical doctors and drug designers. To explore the dynamical features of brain activity in anesthesia, a permutation auto-mutual information (PAMI) method is proposed to measure the information coupling of electroencephalogram (EEG) time series obtained in anesthesia. Approach. The PAMI is developed and applied on EEG data collected from 19 patients under sevoflurane anesthesia. The results are compared with the traditional auto-mutual information (AMI), SynchFastSlow (SFS, derived from the BIS index), permutation entropy (PE), composite PE (CPE), response entropy (RE) and state entropy (SE). Performance of all indices is assessed by pharmacokinetic/pharmacodynamic (PK/PD) modeling and prediction probability. Main results. The PK/PD modeling and prediction probability analysis show that the PAMI index correlates closely with the anesthetic effect. The coefficient of determination R2 between PAMI values and the sevoflurane effect site concentrations, and the prediction probability Pk are higher in comparison with other indices. The information coupling in EEG series can be applied to indicate the effect of the anesthetic drug sevoflurane on the brain activity as well as other indices. The PAMI of the EEG signals is suggested as a new index to track drug concentration change. Significance. The PAMI is a useful index for analyzing the EEG dynamics during general anesthesia.

Validation of brain-derived signals in near-infrared spectroscopy through multivoxel analysis of concurrent functional magnetic resonance imaging.

PubMed

Moriguchi, Yoshiya; Noda, Takamasa; Nakayashiki, Kosei; Takata, Yohei; Setoyama, Shiori; Kawasaki, Shingo; Kunisato, Yoshihiko; Mishima, Kazuo; Nakagome, Kazuyuki; Hanakawa, Takashi

2017-10-01

Near-infrared spectroscopy (NIRS) is a convenient and safe brain-mapping tool. However, its inevitable confounding with hemodynamic responses outside the brain, especially in the frontotemporal head, has questioned its validity. Some researchers attempted to validate NIRS signals through concurrent measurements with functional magnetic resonance imaging (fMRI), but, counterintuitively, NIRS signals rarely correlate with local fMRI signals in NIRS channels, although both mapping techniques should measure the same hemoglobin concentration. Here, we tested a novel hypothesis that different voxels within the scalp and the brain tissues might have substantially different hemoglobin absorption rates of near-infrared light, which might differentially contribute to NIRS signals across channels. Therefore, we newly applied a multivariate approach, a partial least squares regression, to explain NIRS signals with multivoxel information from fMRI within the brain and soft tissues in the head. We concurrently obtained fMRI and NIRS signals in 9 healthy human subjects engaging in an n-back task. The multivariate fMRI model was quite successfully able to predict the NIRS signals by cross-validation (interclass correlation coefficient = ∼0.85). This result confirmed that fMRI and NIRS surely measure the same hemoglobin concentration. Additional application of Monte-Carlo permutation tests confirmed that the model surely reflects temporal and spatial hemodynamic information, not random noise. After this thorough validation, we calculated the ratios of the contributions of the brain and soft-tissue hemodynamics to the NIRS signals, and found that the contribution ratios were quite different across different NIRS channels in reality, presumably because of the structural complexity of the frontotemporal regions. Hum Brain Mapp 38:5274-5291, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Multiple comparisons permutation test for image based data mining in radiotherapy.

PubMed

Chen, Chun; Witte, Marnix; Heemsbergen, Wilma; van Herk, Marcel

2013-12-23

: Comparing incidental dose distributions (i.e. images) of patients with different outcomes is a straightforward way to explore dose-response hypotheses in radiotherapy. In this paper, we introduced a permutation test that compares images, such as dose distributions from radiotherapy, while tackling the multiple comparisons problem. A test statistic Tmax was proposed that summarizes the differences between the images into a single value and a permutation procedure was employed to compute the adjusted p-value. We demonstrated the method in two retrospective studies: a prostate study that relates 3D dose distributions to failure, and an esophagus study that relates 2D surface dose distributions of the esophagus to acute esophagus toxicity. As a result, we were able to identify suspicious regions that are significantly associated with failure (prostate study) or toxicity (esophagus study). Permutation testing allows direct comparison of images from different patient categories and is a useful tool for data mining in radiotherapy.

Permutational symmetries for coincidence rates in multimode multiphotonic interferometry

NASA Astrophysics Data System (ADS)

Khalid, Abdullah; Spivak, Dylan; Sanders, Barry C.; de Guise, Hubert

2018-06-01

We obtain coincidence rates for passive optical interferometry by exploiting the permutational symmetries of partially distinguishable input photons, and our approach elucidates qualitative features of multiphoton coincidence landscapes. We treat the interferometer input as a product state of any number of photons in each input mode with photons distinguished by their arrival time. Detectors at the output of the interferometer count photons from each output mode over a long integration time. We generalize and prove the claim of Tillmann et al. [Phys. Rev. X 5, 041015 (2015), 10.1103/PhysRevX.5.041015] that coincidence rates can be elegantly expressed in terms of immanants. Immanants are functions of matrices that exhibit permutational symmetries and the immanants appearing in our coincidence-rate expressions share permutational symmetries with the input state. Our results are obtained by employing representation theory of the symmetric group to analyze systems of an arbitrary number of photons in arbitrarily sized interferometers.

Systems Maintenance Automated Repair Tasks (SMART)

NASA Technical Reports Server (NTRS)

Schuh, Joseph; Mitchell, Brent; Locklear, Louis; Belson, Martin A.; Al-Shihabi, Mary Jo Y.; King, Nadean; Norena, Elkin; Hardin, Derek

2010-01-01

SMART is a uniform automated discrepancy analysis and repair-authoring platform that improves technical accuracy and timely delivery of repair procedures for a given discrepancy (see figure a). SMART will minimize data errors, create uniform repair processes, and enhance the existing knowledge base of engineering repair processes. This innovation is the first tool developed that links the hardware specification requirements with the actual repair methods, sequences, and required equipment. SMART is flexibly designed to be useable by multiple engineering groups requiring decision analysis, and by any work authorization and disposition platform (see figure b). The organizational logic creates the link between specification requirements of the hardware, and specific procedures required to repair discrepancies. The first segment in the SMART process uses a decision analysis tree to define all the permutations between component/ subcomponent/discrepancy/repair on the hardware. The second segment uses a repair matrix to define what the steps and sequences are for any repair defined in the decision tree. This segment also allows for the selection of specific steps from multivariable steps. SMART will also be able to interface with outside databases and to store information from them to be inserted into the repair-procedure document. Some of the steps will be identified as optional, and would only be used based on the location and the current configuration of the hardware. The output from this analysis would be sent to a work authoring system in the form of a predefined sequence of steps containing required actions, tools, parts, materials, certifications, and specific requirements controlling quality, functional requirements, and limitations.

Higher order explicit symmetric integrators for inseparable forms of coordinates and momenta

NASA Astrophysics Data System (ADS)

Liu, Lei; Wu, Xin; Huang, Guoqing; Liu, Fuyao

2016-06-01

Pihajoki proposed the extended phase-space second-order explicit symmetric leapfrog methods for inseparable Hamiltonian systems. On the basis of this work, we survey a critical problem on how to mix the variables in the extended phase space. Numerical tests show that sequent permutations of coordinates and momenta can make the leapfrog-like methods yield the most accurate results and the optimal long-term stabilized error behaviour. We also present a novel method to construct many fourth-order extended phase-space explicit symmetric integration schemes. Each scheme represents the symmetric production of six usual second-order leapfrogs without any permutations. This construction consists of four segments: the permuted coordinates, triple product of the usual second-order leapfrog without permutations, the permuted momenta and the triple product of the usual second-order leapfrog without permutations. Similarly, extended phase-space sixth, eighth and other higher order explicit symmetric algorithms are available. We used several inseparable Hamiltonian examples, such as the post-Newtonian approach of non-spinning compact binaries, to show that one of the proposed fourth-order methods is more efficient than the existing methods; examples include the fourth-order explicit symplectic integrators of Chin and the fourth-order explicit and implicit mixed symplectic integrators of Zhong et al. Given a moderate choice for the related mixing and projection maps, the extended phase-space explicit symplectic-like methods are well suited for various inseparable Hamiltonian problems. Samples of these problems involve the algorithmic regularization of gravitational systems with velocity-dependent perturbations in the Solar system and post-Newtonian Hamiltonian formulations of spinning compact objects.

Using permutation tests to enhance causal inference in interrupted time series analysis.

PubMed

Linden, Ariel

2018-06-01

Interrupted time series analysis (ITSA) is an evaluation methodology in which a single treatment unit's outcome is studied serially over time and the intervention is expected to "interrupt" the level and/or trend of that outcome. The internal validity is strengthened considerably when the treated unit is contrasted with a comparable control group. In this paper, we introduce a robustness check based on permutation tests to further improve causal inference. We evaluate the effect of California's Proposition 99 for reducing cigarette sales by iteratively casting each nontreated state into the role of "treated," creating a comparable control group using the ITSAMATCH package in Stata, and then evaluating treatment effects using ITSA regression. If statistically significant "treatment effects" are estimated for pseudotreated states, then any significant changes in the outcome of the actual treatment unit (California) cannot be attributed to the intervention. We perform these analyses setting the cutpoint significance level to P > .40 for identifying balanced matches (the highest threshold possible for which controls could still be found for California) and use the difference in differences of trends as the treatment effect estimator. Only California attained a statistically significant treatment effect, strengthening confidence in the conclusion that Proposition 99 reduced cigarette sales. The proposed permutation testing framework provides an additional robustness check to either support or refute a treatment effect identified in for the true treated unit in ITSA. Given its value and ease of implementation, this framework should be considered as a standard robustness test in all multiple group interrupted time series analyses. © 2018 John Wiley & Sons, Ltd.

Spatial structure of helminth communities in the golden grey mullet, Liza aurata (Actinopterygii: Mugilidae), from the Western Mediterranean.

PubMed

Míguez-Lozano, Raúl; Pardo-Carranza, Trinidad V; Blasco-Costa, Isabel; Balbuena, Juan Antonio

2012-10-01

Ecological investigations regarding the parasite fauna of grey mullets are scarce. The present study provides a detailed description of the helminth communities of Liza aurata in the Spanish western Mediterranean and analyzes the role of spatial, temporal, and host variables in shaping the infracommunities. In total, 204 fish were collected in 2 localities, situated ca. 290 km apart, in spring and fall of 2004 and 2005. A non-metric multidimensional scaling (NMDS) was used to visualize an ordination of the infracommunities according to their relative similarities in parasite abundances. The relationship between infracommunity composition and explanatory variables (host size, locality, year, and season of harvest) was examined by permutational analysis of variance (PERMANOVA) applied to species abundances. Permutational tests for homogeneity of multivariate dispersion were used to test the null hypothesis of no differences in dispersion among groups formed by the factors whose effects were significant in PERMANOVA. A total of 33,241 helminth parasites, belonging to 18 species, was collected, i.e., 12 species of adult digeneans (23% of the parasite specimens), 3 digeneans as metacercariae (68%), 1 acanthocephalan (2.1%), and 2 monogeneans (6.5%). An important part of this helminth fauna is specialized to grey mullets, with a sizable portion of the component community restricted to the Mediterranean and northeast Atlantic. The NMDS ordination indicated high heterogeneity among infrapopulations. However, most differences at both the component and infracommunity level were related to geographic locality. In fact, the PERMANOVA showed that, among the explanatory variables considered, sampling locality accounted for the largest share of variation. The geographical differences observed may be related to local environmental characteristics or to the limited spatial dispersal of the species forming the component community. The latter was supported by the significant portion of variation explained by a 3-way interaction term. Thus, the spatial structure of our helminth infracommunities seems to be determined by a combination of differences in local environmental conditions and the transmission ability of each species at small local and time scales.

Parallel approach on sorting of genes in search of optimal solution.

PubMed

Kumar, Pranav; Sahoo, G

2018-05-01

An important tool for comparing genome analysis is the rearrangement event that can transform one given genome into other. For finding minimum sequence of fission and fusion, we have proposed here an algorithm and have shown a transformation example for converting the source genome into the target genome. The proposed algorithm comprises of circular sequence i.e. "cycle graph" in place of mapping. The main concept of algorithm is based on optimal result of permutation. These sorting processes are performed in constant running time by showing permutation in the form of cycle. In biological instances it has been observed that transposition occurs half of the frequency as that of reversal. In this paper we are not dealing with reversal instead commencing with the rearrangement of fission, fusion as well as transposition. Copyright © 2017 Elsevier Inc. All rights reserved.

Search Interface Design Using Faceted Indexing for Web Resources.

ERIC Educational Resources Information Center

Devadason, Francis; Intaraksa, Neelawat; Patamawongjariya, Pornprapa; Desai, Kavita

2001-01-01

Describes an experimental system designed to organize and provide access to Web documents using a faceted pre-coordinate indexing system based on the Deep Structure Indexing System (DSIS) derived from POPSI (Postulate based Permuted Subject Indexing) of Bhattacharyya, and the facet analysis and chain indexing system of Ranganathan. (AEF)

Sylow p-groups of polynomial permutations on the integers mod pn☆

PubMed Central

Frisch, Sophie; Krenn, Daniel

2013-01-01

We enumerate and describe the Sylow p-groups of the groups of polynomial permutations of the integers mod pn for n⩾1 and of the pro-finite group which is the projective limit of these groups. PMID:26869732

Storage and computationally efficient permutations of factorized covariance and square-root information arrays

NASA Technical Reports Server (NTRS)

Muellerschoen, R. J.

1988-01-01

A unified method to permute vector stored Upper triangular Diagonal factorized covariance and vector stored upper triangular Square Root Information arrays is presented. The method involves cyclic permutation of the rows and columns of the arrays and retriangularization with fast (slow) Givens rotations (reflections). Minimal computation is performed, and a one dimensional scratch array is required. To make the method efficient for large arrays on a virtual memory machine, computations are arranged so as to avoid expensive paging faults. This method is potentially important for processing large volumes of radio metric data in the Deep Space Network.

Note on new KLT relations

NASA Astrophysics Data System (ADS)

Feng, Bo; He, Song; Huang, Rijun; Jia, Yin

2010-10-01

In this short note, we present two results about KLT relations discussed in recent several papers. Our first result is the re-derivation of Mason-Skinner MHV amplitude by applying the S n-3 permutation symmetric KLT relations directly to MHV amplitude. Our second result is the equivalence proof of the newly discovered S n-2 permutation symmetric KLT relations and the well-known S n-3 permutation symmetric KLT relations. Although both formulas have been shown to be correct by BCFW recursion relations, our result is the first direct check using the regularized definition of the new formula.

Combating HER2-overexpressing breast cancer through induction of calreticulin exposure by Tras-Permut CrossMab

PubMed Central

Zhang, Fan; Zhang, Jie; Liu, Moyan; Zhao, Lichao; LingHu, RuiXia; Feng, Fan; Gao, Xudong; Jiao, Shunchang; Zhao, Lei; Hu, Yi; Yang, Junlan

2015-01-01

Although trastuzumab has succeeded in breast cancer treatment, acquired resistance is one of the prime obstacles for breast cancer therapies. There is an urgent need to develop novel HER2 antibodies against trastuzumab resistance. Here, we first rational designed avidity-imporved trastuzumab and pertuzumab variants, and explored the correlation between the binding avidity improvement and their antitumor activities. After characterization of a pertuzumab variant L56TY with potent antitumor activities, a bispecific immunoglobulin G-like CrossMab (Tras-Permut CrossMab) was generated from trastuzumab and binding avidity-improved pertuzumab variant L56TY. Although, the antitumor efficacy of trastuzumab was not enhanced by improving its binding avidity, binding avidity improvement could significantly increase the anti-proliferative and antibody-dependent cellular cytotoxicity (ADCC) activities of pertuzumab. Further studies showed that Tras-Permut CrossMab exhibited exceptional high efficiency to inhibit the progression of trastuzumab-resistant breast cancer. Notably, we found that calreticulin (CRT) exposure induced by Tras-Permut CrossMab was essential for induction of tumor-specific T cell immunity against tumor recurrence. These data indicated that simultaneous blockade of HER2 protein by Tras-Permut CrossMab could trigger CRT exposure and subsequently induce potent tumor-specific T cell immunity, suggesting it could be a promising therapeutic strategy against trastuzumab resistance. PMID:25949918

Automatic NEPHIS Coding of Descriptive Titles for Permuted Index Generation.

ERIC Educational Resources Information Center

Craven, Timothy C.

1982-01-01

Describes a system for the automatic coding of most descriptive titles which generates Nested Phrase Indexing System (NEPHIS) input strings of sufficient quality for permuted index production. A series of examples and an 11-item reference list accompany the text. (JL)

Following healthy pregnancy by nuclear magnetic resonance (NMR) metabolic profiling of human urine.

PubMed

Diaz, Sílvia O; Barros, António S; Goodfellow, Brian J; Duarte, Iola F; Carreira, Isabel M; Galhano, Eulália; Pita, Cristina; Almeida, Maria do Céu; Gil, Ana M

2013-02-01

In this work, untargeted NMR metabonomics was employed to evaluate the effects of pregnancy on the metabolite composition of maternal urine, thus establishing a control excretory trajectory for healthy pregnancies. Urine was collected for independent groups of healthy nonpregnant and pregnant women (in first, second, third trimesters) and multivariate analysis performed on the corresponding NMR spectra. Models were validated through Monte Carlo Cross Validation and permutation tests and metabolite correlations measured through Statistical Total Correlation Spectroscopy. The levels of 21 metabolites were found to change significantly throughout pregnancy, with variations observed for the first time to our knowledge for choline, creatinine, 4-deoxyerythronic acid, 4-deoxythreonic acid, furoylglycine, guanidoacetate, 3-hydroxybutyrate, and lactate. Results confirmed increased aminoaciduria across pregnancy and suggested (a) a particular involvement of isoleucine and threonine in lipid oxidation/ketone body synthesis, (b) a relation of excreted choline, taurine, and guanidoacetate to methionine metabolism and urea cycle regulation, and (c) a possible relationship of furoylglycine and creatinine to pregnancy, based on a tandem study of nonfasting confounding effects. Results demonstrate the usefulness of untargeted metabonomics in finding biomarker metabolic signatures for healthy pregnancies, against which disease-related deviations may be confronted in future studies, as a base for improved diagnostics and prediction.

Minerals in soil select distinct bacterial communities in their microhabitats.

PubMed

Carson, Jennifer K; Campbell, Louise; Rooney, Deirdre; Clipson, Nicholas; Gleeson, Deirdre B

2009-03-01

We tested the hypothesis that different minerals in soil select distinct bacterial communities in their microhabitats. Mica (M), basalt (B) and rock phosphate (RP) were incubated separately in soil planted with Trifolium subterraneum, Lolium rigidum or left unplanted. After 70 days, the mineral and soil fractions were separated by sieving. Automated ribosomal intergenic spacer analysis was used to determine whether the bacterial community structure was affected by the mineral, fraction and plant treatments. Principal coordinate plots showed clustering of bacterial communities from different fraction and mineral treatments, but not from different plant treatments. Permutational multivariate anova (permanova) showed that the microhabitats of M, B and RP selected bacterial communities different from each other in unplanted and L. rigidum, and in T. subterraneum, bacterial communities from M and B differed (P<0.046). permanova also showed that each mineral fraction selected bacterial communities different from the surrounding soil fraction (P<0.05). This study shows that the structure of bacterial communities in soil is influenced by the mineral substrates in their microhabitat and that minerals in soil play a greater role in bacterial ecology than simply providing an inert matrix for bacterial growth. This study suggests that mineral heterogeneity in soil contributes to the spatial variation in bacterial communities.

Cadaver Thanatomicrobiome Signatures: The Ubiquitous Nature of Clostridium Species in Human Decomposition.

PubMed

Javan, Gulnaz T; Finley, Sheree J; Smith, Tasia; Miller, Joselyn; Wilkinson, Jeremy E

2017-01-01

Human thanatomicrobiome studies have established that an abundant number of putrefactive bacteria within internal organs of decaying bodies are obligate anaerobes, Clostridium spp. These microorganisms have been implicated as etiological agents in potentially life-threatening infections; notwithstanding, the scale and trajectory of these microbes after death have not been elucidated. We performed phylogenetic surveys of thanatomicrobiome signatures of cadavers' internal organs to compare the microbial diversity between the 16S rRNA gene V4 hypervariable region and V3-4 conjoined regions from livers and spleens of 45 cadavers undergoing forensic microbiological studies. Phylogenetic analyses of 16S rRNA gene sequences revealed that the V4 region had a significantly higher mean Chao1 richness within the total microbiome data. Permutational multivariate analysis of variance statistical tests, based on unweighted UniFrac distances, demonstrated that taxa compositions were significantly different between V4 and V3-4 hypervariable regions ( p < 0.001). Of note, we present the first study, using the largest cohort of criminal cases to date, that two hypervariable regions show discriminatory power for human postmortem microbial diversity. In conclusion, here we propose the impact of hypervariable region selection for the 16S rRNA gene in differentiating thanatomicrobiomic profiles to provide empirical data to explain a unique concept, the Postmortem Clostridium Effect.

Namib Desert edaphic bacterial, fungal and archaeal communities assemble through deterministic processes but are influenced by different abiotic parameters.

PubMed

Johnson, Riegardt M; Ramond, Jean-Baptiste; Gunnigle, Eoin; Seely, Mary; Cowan, Don A

2017-03-01

The central Namib Desert is hyperarid, where limited plant growth ensures that biogeochemical processes are largely driven by microbial populations. Recent research has shown that niche partitioning is critically involved in the assembly of Namib Desert edaphic communities. However, these studies have mainly focussed on the Domain Bacteria. Using microbial community fingerprinting, we compared the assembly of the bacterial, fungal and archaeal populations of microbial communities across nine soil niches from four Namib Desert soil habitats (riverbed, dune, gravel plain and salt pan). Permutational multivariate analysis of variance indicated that the nine soil niches presented significantly different physicochemistries (R 2  = 0.8306, P ≤ 0.0001) and that bacterial, fungal and archaeal populations were soil niche specific (R 2  ≥ 0.64, P ≤ 0.001). However, the abiotic drivers of community structure were Domain-specific (P < 0.05), with P, clay and sand fraction, and NH 4 influencing bacterial, fungal and archaeal communities, respectively. Soil physicochemistry and soil niche explained over 50% of the variation in community structure, and communities displayed strong non-random patterns of co-occurrence. Taken together, these results demonstrate that in central Namib Desert soil microbial communities, assembly is principally driven by deterministic processes.

Enteral tube feeding alters the oral indigenous microbiota in elderly adults.

PubMed

Takeshita, Toru; Yasui, Masaki; Tomioka, Mikiko; Nakano, Yoshio; Shimazaki, Yoshihiro; Yamashita, Yoshihisa

2011-10-01

Enteral tube feeding is widely used to maintain nutrition for elderly adults with eating difficulties, but its long-term use alters the environment of the oral ecosystem. This study characterized the tongue microbiota of tube-fed elderly adults by analyzing the 16S rRNA gene. The terminal restriction fragment length polymorphism (T-RFLP) profiles of 44 tube-fed subjects were compared with those of 54 subjects fed orally (average age, 86.4 ± 6.9 years). Bar-coded pyrosequencing data were also obtained for a subset of the subjects from each group (15 tube-fed subjects and 16 subjects fed orally). The T-RFLP profiles demonstrated that the microbiota of the tube-fed subjects was distinct from that of the subjects fed orally (permutational multivariate analysis of variance [perMANOVA], P < 0.001). The pyrosequencing data revealed that 22 bacterial genera, including Corynebacterium, Peptostreptococcus, and Fusobacterium, were significantly more predominant in tube-fed subjects, whereas the dominant genera in the subjects fed orally, such as Streptococcus and Veillonella, were present in much lower proportions. Opportunistic pathogens rarely detected in the normal oral microbiota, such as Corynebacterium striatum and Streptococcus agalactiae, were often found in high proportions in tube-fed subjects. The oral indigenous microbiota is disrupted by the use of enteral feeding, allowing health-threatening bacteria to thrive.

Diagnostic index of three-dimensional osteoarthritic changes in temporomandibular joint condylar morphology

PubMed Central

Gomes, Liliane R.; Gomes, Marcelo; Jung, Bryan; Paniagua, Beatriz; Ruellas, Antonio C.; Gonçalves, João Roberto; Styner, Martin A.; Wolford, Larry; Cevidanes, Lucia

2015-01-01

Abstract. This study aimed to investigate imaging statistical approaches for classifying three-dimensional (3-D) osteoarthritic morphological variations among 169 temporomandibular joint (TMJ) condyles. Cone-beam computed tomography scans were acquired from 69 subjects with long-term TMJ osteoarthritis (OA), 15 subjects at initial diagnosis of OA, and 7 healthy controls. Three-dimensional surface models of the condyles were constructed and SPHARM-PDM established correspondent points on each model. Multivariate analysis of covariance and direction-projection-permutation (DiProPerm) were used for testing statistical significance of the differences between the groups determined by clinical and radiographic diagnoses. Unsupervised classification using hierarchical agglomerative clustering was then conducted. Compared with healthy controls, OA average condyle was significantly smaller in all dimensions except its anterior surface. Significant flattening of the lateral pole was noticed at initial diagnosis. We observed areas of 3.88-mm bone resorption at the superior surface and 3.10-mm bone apposition at the anterior aspect of the long-term OA average model. DiProPerm supported a significant difference between the healthy control and OA group (p-value=0.001). Clinically meaningful unsupervised classification of TMJ condylar morphology determined a preliminary diagnostic index of 3-D osteoarthritic changes, which may be the first step towards a more targeted diagnosis of this condition. PMID:26158119

Unbiased plasma metabolomics reveal the correlation of metabolic pathways and Prakritis of humans.

PubMed

Shirolkar, Amey; Chakraborty, Sutapa; Mandal, Tusharkanti; Dabur, Rajesh

2017-11-25

Ayurveda, an ancient Indian medicinal system, has categorized human body constitutions in three broad constitutional types (prakritis) i.e. Vata, Pitta and Kapha. Analysis of plasma metabolites and related pathways to classify Prakriti specific dominant marker metabolites and metabolic pathways. 38 healthy male individuals were assessed for dominant Prakritis and their fasting blood samples were collected. The processed plasma samples were subjected to rapid resolution liquid chromatography-electrospray ionization-quadrupole time of flight mass spectrometry (RRLC-ESI-QTOFMS). Mass profiles were aligned and subjected to multivariate analysis. Partial least square discriminant analysis (PLS-DA) model showed 97.87% recognition capability. List of PLS-DA metabolites was subjected to permutative Benjamini-Hochberg false discovery rate (FDR) correction and final list of 76 metabolites with p < 0.05 and fold-change > 2.0 was identified. Pathway analysis using metascape and JEPETTO plugins in Cytoscape revealed that steroidal hormone biosynthesis, amino acid, and arachidonic acid metabolism are major pathways varying with different constitution. Biological Go processes analysis showed that aromatic amino acids, sphingolipids, and pyrimidine nucleotides metabolic processes were dominant in kapha type of body constitution. Fat soluble vitamins, cellular amino acid, and androgen biosynthesis process along with branched chain amino acid and glycerolipid catabolic processes were dominant in pitta type individuals. Vata Prakriti was found to have dominant catecholamine, arachidonic acid and hydrogen peroxide metabolomics processes. The neurotransmission and oxidative stress in vata, BCAA catabolic, androgen, xenobiotics metabolic processes in pitta, and aromatic amino acids, sphingolipid, and pyrimidine metabolic process in kaphaPrakriti were the dominant marker pathways. Copyright © 2017 Transdisciplinary University, Bangalore and World Ayurveda Foundation. Published by Elsevier B.V. All rights reserved.

Creation of a Ligand-Dependent Enzyme by Fusing Circularly Permuted Antibody Variable Region Domains.

PubMed

Iwai, Hiroto; Kojima-Misaizu, Miki; Dong, Jinhua; Ueda, Hiroshi

2016-04-20

Allosteric control of enzyme activity with exogenous substances has been hard to achieve, especially using antibody domains that potentially allow control by any antigens of choice. Here, in order to attain this goal, we developed a novel antibody variable region format introduced with circular permutations, called Clampbody. The two variable-region domains of the antibone Gla protein (BGP) antibody were each circularly permutated to have novel termini at the loops near their domain interface. Through their attachment to the N- and C-termini of a circularly permutated TEM-1 β-lactamase (cpBLA), we created a molecular switch that responds to the antigen peptide. The fusion protein specifically recognized the antigen, and in the presence of some detergent or denaturant, its catalytic activity was enhanced up to 4.7-fold in an antigen-dependent manner, due to increased resistance to these reagents. Hence, Clampbody will be a powerful tool for the allosteric regulation of enzyme and other protein activities and especially useful to design robust biosensors.

Multiple comparisons permutation test for image based data mining in radiotherapy

PubMed Central

2013-01-01

Comparing incidental dose distributions (i.e. images) of patients with different outcomes is a straightforward way to explore dose-response hypotheses in radiotherapy. In this paper, we introduced a permutation test that compares images, such as dose distributions from radiotherapy, while tackling the multiple comparisons problem. A test statistic Tmax was proposed that summarizes the differences between the images into a single value and a permutation procedure was employed to compute the adjusted p-value. We demonstrated the method in two retrospective studies: a prostate study that relates 3D dose distributions to failure, and an esophagus study that relates 2D surface dose distributions of the esophagus to acute esophagus toxicity. As a result, we were able to identify suspicious regions that are significantly associated with failure (prostate study) or toxicity (esophagus study). Permutation testing allows direct comparison of images from different patient categories and is a useful tool for data mining in radiotherapy. PMID:24365155

Quantum one-way permutation over the finite field of two elements

NASA Astrophysics Data System (ADS)

de Castro, Alexandre

2017-06-01

In quantum cryptography, a one-way permutation is a bounded unitary operator U:{H} → {H} on a Hilbert space {H} that is easy to compute on every input, but hard to invert given the image of a random input. Levin (Probl Inf Transm 39(1):92-103, 2003) has conjectured that the unitary transformation g(a,x)=(a,f(x)+ax), where f is any length-preserving function and a,x \\in {GF}_{{2}^{\\Vert x\\Vert }}, is an information-theoretically secure operator within a polynomial factor. Here, we show that Levin's one-way permutation is provably secure because its output values are four maximally entangled two-qubit states, and whose probability of factoring them approaches zero faster than the multiplicative inverse of any positive polynomial poly( x) over the Boolean ring of all subsets of x. Our results demonstrate through well-known theorems that existence of classical one-way functions implies existence of a universal quantum one-way permutation that cannot be inverted in subexponential time in the worst case.

Correntropy-based partial directed coherence for testing multivariate Granger causality in nonlinear processes

NASA Astrophysics Data System (ADS)

Kannan, Rohit; Tangirala, Arun K.

2014-06-01

Identification of directional influences in multivariate systems is of prime importance in several applications of engineering and sciences such as plant topology reconstruction, fault detection and diagnosis, and neurosciences. A spectrum of related directionality measures, ranging from linear measures such as partial directed coherence (PDC) to nonlinear measures such as transfer entropy, have emerged over the past two decades. The PDC-based technique is simple and effective, but being a linear directionality measure has limited applicability. On the other hand, transfer entropy, despite being a robust nonlinear measure, is computationally intensive and practically implementable only for bivariate processes. The objective of this work is to develop a nonlinear directionality measure, termed as KPDC, that possesses the simplicity of PDC but is still applicable to nonlinear processes. The technique is founded on a nonlinear measure called correntropy, a recently proposed generalized correlation measure. The proposed method is equivalent to constructing PDC in a kernel space where the PDC is estimated using a vector autoregressive model built on correntropy. A consistent estimator of the KPDC is developed and important theoretical results are established. A permutation scheme combined with the sequential Bonferroni procedure is proposed for testing hypothesis on absence of causality. It is demonstrated through several case studies that the proposed methodology effectively detects Granger causality in nonlinear processes.

Discrete Bat Algorithm for Optimal Problem of Permutation Flow Shop Scheduling

PubMed Central

Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang

2014-01-01

A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem. PMID:25243220

Discrete bat algorithm for optimal problem of permutation flow shop scheduling.

PubMed

Luo, Qifang; Zhou, Yongquan; Xie, Jian; Ma, Mingzhi; Li, Liangliang

2014-01-01

A discrete bat algorithm (DBA) is proposed for optimal permutation flow shop scheduling problem (PFSP). Firstly, the discrete bat algorithm is constructed based on the idea of basic bat algorithm, which divide whole scheduling problem into many subscheduling problems and then NEH heuristic be introduced to solve subscheduling problem. Secondly, some subsequences are operated with certain probability in the pulse emission and loudness phases. An intensive virtual population neighborhood search is integrated into the discrete bat algorithm to further improve the performance. Finally, the experimental results show the suitability and efficiency of the present discrete bat algorithm for optimal permutation flow shop scheduling problem.

Multiscale permutation entropy analysis of laser beam wandering in isotropic turbulence.

PubMed

Olivares, Felipe; Zunino, Luciano; Gulich, Damián; Pérez, Darío G; Rosso, Osvaldo A

2017-10-01

We have experimentally quantified the temporal structural diversity from the coordinate fluctuations of a laser beam propagating through isotropic optical turbulence. The main focus here is on the characterization of the long-range correlations in the wandering of a thin Gaussian laser beam over a screen after propagating through a turbulent medium. To fulfill this goal, a laboratory-controlled experiment was conducted in which coordinate fluctuations of the laser beam were recorded at a sufficiently high sampling rate for a wide range of turbulent conditions. Horizontal and vertical displacements of the laser beam centroid were subsequently analyzed by implementing the symbolic technique based on ordinal patterns to estimate the well-known permutation entropy. We show that the permutation entropy estimations at multiple time scales evidence an interplay between different dynamical behaviors. More specifically, a crossover between two different scaling regimes is observed. We confirm a transition from an integrated stochastic process contaminated with electronic noise to a fractional Brownian motion with a Hurst exponent H=5/6 as the sampling time increases. Besides, we are able to quantify, from the estimated entropy, the amount of electronic noise as a function of the turbulence strength. We have also demonstrated that these experimental observations are in very good agreement with numerical simulations of noisy fractional Brownian motions with a well-defined crossover between two different scaling regimes.

Fecal Microbiota Characteristics of Patients with Colorectal Adenoma Detected by Screening: A Population-based Study

PubMed Central

Goedert, James J.; Gong, Yangming; Hua, Xing; Zhong, Huanzi; He, Yimin; Peng, Peng; Yu, Guoqin; Wang, Wenjing; Ravel, Jacques; Shi, Jianxin; Zheng, Ying

2015-01-01

Background Screening for colorectal cancer (CRC) and precancerous colorectal adenoma (CRA) can detect curable disease. However, participation in colonoscopy and sensitivity of fecal heme for CRA are low. Methods Microbiota metrics were determined by Illumina sequencing of 16S rRNA genes amplified from DNA extracted from feces self-collected in RNAlater. Among fecal immunochemical test-positive (FIT +) participants, colonoscopically-defined normal versus CRA patients were compared by regression, permutation, and random forest plus leave-one-out methods. Findings Of 95 FIT + participants, 61 had successful fecal microbiota profiling and colonoscopy, identifying 24 completely normal patients, 20 CRA patients, 2 CRC patients, and 15 with other conditions. Phylum-level fecal community composition differed significantly between CRA and normal patients (permutation P = 0.02). Rank phylum-level abundance distinguished CRA from normal patients (area under the curve = 0.767, permutation P = 0.006). CRA prevalence was 59% in phylum-level cluster B versus 20% in cluster A (exact P = 0.01). Most of the difference reflected 3-fold higher median relative abundance of Proteobacteria taxa (Wilcoxon signed-rank P = 0.03, positive predictive value = 67%). Antibiotic exposure and other potential confounders did not affect the associations. Interpretation If confirmed in larger, more diverse populations, fecal microbiota analysis might be employed to improve screening for CRA and ultimately to reduce mortality from CRC. PMID:26288821

Effectiveness of qPCR permutations, internal controls and dilution as means for minimizing the impact of inhibition while measuring Enterococcus in environmental waters.

PubMed

Cao, Y; Griffith, J F; Dorevitch, S; Weisberg, S B

2012-07-01

  Draft criteria for the optional use of qPCR for recreational water quality monitoring have been published in the United States. One concern is that inhibition of the qPCR assay can lead to false-negative results and potentially inadequate public health protection. We evaluate the effectiveness of strategies for minimizing the impact of inhibition.   Five qPCR method permutations for measuring Enterococcus were challenged with 133 potentially inhibitory fresh and marine water samples. Serial dilutions were conducted to assess Enterococcus target assay inhibition, to which inhibition identified using four internal controls (IC) was compared. The frequency and magnitude of inhibition varied considerably among qPCR methods, with the permutation using an environmental master mix performing substantially better. Fivefold dilution was also effective at reducing inhibition in most samples (>78%). ICs were variable and somewhat ineffective, with 54-85% agreement between ICs and serial dilution.   The current IC methods appear to not accurately predict Enterococcus inhibition and should be used with caution; fivefold dilution and the use of reagents designed for environmental sample analysis (i.e. more robust qPCR chemistry) may be preferable.   Suitable approaches for defining, detecting and reducing inhibition will improve implementation of qPCR for water monitoring. © 2012 The Authors. Journal of Applied Microbiology © 2012 The Society for Applied Microbiology.

Levels of Conceptual Development in Melodic Permutation Concepts Based on Piaget's Theory

ERIC Educational Resources Information Center

Larn, Ronald L.

1973-01-01

Article considered different ways in which subjects at different age levels solved a musical task involving melodic permutation. The differences in responses to the musical task between age groups were judged to be compatible with Piaget's theory of cognitive development. (Author/RK)

In Response to Rowland on "Realism and Debateability in Policy Advocacy."

ERIC Educational Resources Information Center

Herbeck, Dale A.; Katsulas, John P.

1986-01-01

Argues that Robert Rowland has overstated the case against the permutation process for assessing counterplan competitiveness. Claims that the permutation standard is a viable method for ascertaining counterplan competitiveness. Examines Rowland's alternative and argues that it is an unsatisfactory method for determining counterplan…

Monitoring the informational efficiency of European corporate bond markets with dynamical permutation min-entropy

NASA Astrophysics Data System (ADS)

Zunino, Luciano; Bariviera, Aurelio F.; Guercio, M. Belén; Martinez, Lisana B.; Rosso, Osvaldo A.

2016-08-01

In this paper the permutation min-entropy has been implemented to unveil the presence of temporal structures in the daily values of European corporate bond indices from April 2001 to August 2015. More precisely, the informational efficiency evolution of the prices of fifteen sectorial indices has been carefully studied by estimating this information-theory-derived symbolic tool over a sliding time window. Such a dynamical analysis makes possible to obtain relevant conclusions about the effect that the 2008 credit crisis has had on the different European corporate bond sectors. It is found that the informational efficiency of some sectors, namely banks, financial services, insurance, and basic resources, has been strongly reduced due to the financial crisis whereas another set of sectors, integrated by chemicals, automobiles, media, energy, construction, industrial goods & services, technology, and telecommunications has only suffered a transitory loss of efficiency. Last but not least, the food & beverage, healthcare, and utilities sectors show a behavior close to a random walk practically along all the period of analysis, confirming a remarkable immunity against the 2008 financial crisis.

EPEPT: A web service for enhanced P-value estimation in permutation tests

PubMed Central

2011-01-01

Background In computational biology, permutation tests have become a widely used tool to assess the statistical significance of an event under investigation. However, the common way of computing the P-value, which expresses the statistical significance, requires a very large number of permutations when small (and thus interesting) P-values are to be accurately estimated. This is computationally expensive and often infeasible. Recently, we proposed an alternative estimator, which requires far fewer permutations compared to the standard empirical approach while still reliably estimating small P-values [1]. Results The proposed P-value estimator has been enriched with additional functionalities and is made available to the general community through a public website and web service, called EPEPT. This means that the EPEPT routines can be accessed not only via a website, but also programmatically using any programming language that can interact with the web. Examples of web service clients in multiple programming languages can be downloaded. Additionally, EPEPT accepts data of various common experiment types used in computational biology. For these experiment types EPEPT first computes the permutation values and then performs the P-value estimation. Finally, the source code of EPEPT can be downloaded. Conclusions Different types of users, such as biologists, bioinformaticians and software engineers, can use the method in an appropriate and simple way. Availability http://informatics.systemsbiology.net/EPEPT/ PMID:22024252

Molecular symmetry: Why permutation-inversion (PI) groups don't render the point groups obsolete

NASA Astrophysics Data System (ADS)

Groner, Peter

2018-01-01

The analysis of spectra of molecules with internal large-amplitude motions (LAMs) requires molecular symmetry (MS) groups that are larger than and significantly different from the more familiar point groups. MS groups are described often by the permutation-inversion (PI) group method. It is shown that point groups still can and should play a significant role together with the PI groups for a class of molecules with internal rotors. In molecules of this class, several simple internal rotors are attached to a rigid molecular frame. The PI groups for this class are semidirect products like H ^ F, where the invariant subgroup H is a direct product of cyclic groups and F is a point group. This result is used to derive meaningful labels for MS groups, and to derive correlation tables between MS groups and point groups. MS groups of this class have many parallels to space groups of crystalline solids.

An efficient genome-wide association test for mixed binary and continuous phenotypes with applications to substance abuse research.

PubMed

Buu, Anne; Williams, L Keoki; Yang, James J

2018-03-01

We propose a new genome-wide association test for mixed binary and continuous phenotypes that uses an efficient numerical method to estimate the empirical distribution of the Fisher's combination statistic under the null hypothesis. Our simulation study shows that the proposed method controls the type I error rate and also maintains its power at the level of the permutation method. More importantly, the computational efficiency of the proposed method is much higher than the one of the permutation method. The simulation results also indicate that the power of the test increases when the genetic effect increases, the minor allele frequency increases, and the correlation between responses decreases. The statistical analysis on the database of the Study of Addiction: Genetics and Environment demonstrates that the proposed method combining multiple phenotypes can increase the power of identifying markers that may not be, otherwise, chosen using marginal tests.

Mass univariate analysis of event-related brain potentials/fields I: a critical tutorial review.

PubMed

Groppe, David M; Urbach, Thomas P; Kutas, Marta

2011-12-01

Event-related potentials (ERPs) and magnetic fields (ERFs) are typically analyzed via ANOVAs on mean activity in a priori windows. Advances in computing power and statistics have produced an alternative, mass univariate analyses consisting of thousands of statistical tests and powerful corrections for multiple comparisons. Such analyses are most useful when one has little a priori knowledge of effect locations or latencies, and for delineating effect boundaries. Mass univariate analyses complement and, at times, obviate traditional analyses. Here we review this approach as applied to ERP/ERF data and four methods for multiple comparison correction: strong control of the familywise error rate (FWER) via permutation tests, weak control of FWER via cluster-based permutation tests, false discovery rate control, and control of the generalized FWER. We end with recommendations for their use and introduce free MATLAB software for their implementation. Copyright © 2011 Society for Psychophysiological Research.

Entanglement distillation protocols and number theory

NASA Astrophysics Data System (ADS)

Bombin, H.; Martin-Delgado, M. A.

2005-09-01

We show that the analysis of entanglement distillation protocols for qudits of arbitrary dimension D benefits from applying basic concepts from number theory, since the set ZDn associated with Bell diagonal states is a module rather than a vector space. We find that a partition of ZDn into divisor classes characterizes the invariant properties of mixed Bell diagonal states under local permutations. We construct a very general class of recursion protocols by means of unitary operations implementing these local permutations. We study these distillation protocols depending on whether we use twirling operations in the intermediate steps or not, and we study them both analytically and numerically with Monte Carlo methods. In the absence of twirling operations, we construct extensions of the quantum privacy algorithms valid for secure communications with qudits of any dimension D . When D is a prime number, we show that distillation protocols are optimal both qualitatively and quantitatively.

Analysis of genome rearrangement by block-interchanges.

PubMed

Lu, Chin Lung; Lin, Ying Chih; Huang, Yen Lin; Tang, Chuan Yi

2007-01-01

Block-interchanges are a new kind of genome rearrangements that affect the gene order in a chromosome by swapping two nonintersecting blocks of genes of any length. More recently, the study of such rearrangements is becoming increasingly important because of its applications in molecular evolution. Usually, this kind of study requires to solve a combinatorial problem, called the block-interchange distance problem, which is to find a minimum number of block-interchanges between two given gene orders of linear/circular chromosomes to transform one gene order into another. In this chapter, we shall introduce the basics of block-interchange rearrangements and permutation groups in algebra that are useful in analyses of genome rearrangements. In addition, we shall present a simple algorithm on the basis of permutation groups to efficiently solve the block-interchange distance problem, as well as ROBIN, a web server for the online analyses of block-interchange rearrangements.

regioneR: an R/Bioconductor package for the association analysis of genomic regions based on permutation tests.

PubMed

Gel, Bernat; Díez-Villanueva, Anna; Serra, Eduard; Buschbeck, Marcus; Peinado, Miguel A; Malinverni, Roberto

2016-01-15

Statistically assessing the relation between a set of genomic regions and other genomic features is a common challenging task in genomic and epigenomic analyses. Randomization based approaches implicitly take into account the complexity of the genome without the need of assuming an underlying statistical model. regioneR is an R package that implements a permutation test framework specifically designed to work with genomic regions. In addition to the predefined randomization and evaluation strategies, regioneR is fully customizable allowing the use of custom strategies to adapt it to specific questions. Finally, it also implements a novel function to evaluate the local specificity of the detected association. regioneR is an R package released under Artistic-2.0 License. The source code and documents are freely available through Bioconductor (http://www.bioconductor.org/packages/regioneR). rmalinverni@carrerasresearch.org. © The Author 2015. Published by Oxford University Press.

Vascular tone pathway polymorphisms in relation to primary open-angle glaucoma.

PubMed

Kang, J H; Loomis, S J; Yaspan, B L; Bailey, J C; Weinreb, R N; Lee, R K; Lichter, P R; Budenz, D L; Liu, Y; Realini, T; Gaasterland, D; Gaasterland, T; Friedman, D S; McCarty, C A; Moroi, S E; Olson, L; Schuman, J S; Singh, K; Vollrath, D; Wollstein, G; Zack, D J; Brilliant, M; Sit, A J; Christen, W G; Fingert, J; Forman, J P; Buys, E S; Kraft, P; Zhang, K; Allingham, R R; Pericak-Vance, M A; Richards, J E; Hauser, M A; Haines, J L; Wiggs, J L; Pasquale, L R

2014-06-01

Vascular perfusion may be impaired in primary open-angle glaucoma (POAG); thus, we evaluated a panel of markers in vascular tone-regulating genes in relation to POAG. We used Illumina 660W-Quad array genotype data and pooled P-values from 3108 POAG cases and 3430 controls from the combined National Eye Institute Glaucoma Human Genetics Collaboration consortium and Glaucoma Genes and Environment studies. Using information from previous literature and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, we compiled single-nucleotide polymorphisms (SNPs) in 186 vascular tone-regulating genes. We used the 'Pathway Analysis by Randomization Incorporating Structure' analysis software, which performed 1000 permutations to compare the overall pathway and selected genes with comparable randomly generated pathways and genes in their association with POAG. The vascular tone pathway was not associated with POAG overall or POAG subtypes, defined by the type of visual field loss (early paracentral loss (n=224 cases) or only peripheral loss (n=993 cases)) (permuted P≥0.20). In gene-based analyses, eight were associated with POAG overall at permuted P<0.001: PRKAA1, CAV1, ITPR3, EDNRB, GNB2, DNM2, HFE, and MYL9. Notably, six of these eight (the first six listed) code for factors involved in the endothelial nitric oxide synthase activity, and three of these six (CAV1, ITPR3, and EDNRB) were also associated with early paracentral loss at P<0.001, whereas none of the six genes reached P<0.001 for peripheral loss only. Although the assembled vascular tone SNP set was not associated with POAG, genes that code for local factors involved in setting vascular tone were associated with POAG.

Intestinal Microbiota Signatures Associated With Histological Liver Steatosis in Pediatric-Onset Intestinal Failure.

PubMed

Korpela, Katri; Mutanen, Annika; Salonen, Anne; Savilahti, Erkki; de Vos, Willem M; Pakarinen, Mikko P

2017-02-01

Intestinal failure (IF)-associated liver disease (IFALD) is the major cause of mortality in IF. The link between intestinal microbiota and IFALD is unclear. We compared intestinal microbiota of patients with IF (n = 23) with healthy controls (n = 58) using culture-independent phylogenetic microarray analysis. The microbiota was related to histological liver injury, fecal markers of intestinal inflammation, matrix metalloproteinase 9 and calprotectin, and disease characteristics. Overabundance of Lactobacilli, Proteobacteria, and Actinobacteria was observed in IF, whereas bacteria related to Clostridium clusters III, IV, and XIVa along with overall diversity and richness were reduced. Patients were segregated into 3 subgroups based on dominating bacteria: Clostridium cluster XIVa, Proteobacteria, and bacteria related to Lactobacillus plantarum. In addition to liver steatosis and fibrosis, Proteobacteria were associated with prolonged current parenteral nutrition (PN) as well as liver and intestinal inflammation. Lactobacilli were related to advanced steatosis and fibrosis mostly after weaning off PN without associated inflammation. In multivariate permutational analysis of variance, liver steatosis, bowel length, PN calories, and antibiotic treatment best explained the microbiota variation among patients with IF. Intestinal microbiota composition was associated with liver steatosis in IF and better predicted steatosis than duration of PN or length of the remaining intestine. Our results may be explained by a model in which steatosis is initiated during PN in response to proinflammatory lipopolysaccharides produced by Proteobacteria and progresses after weaning off PN, as the L plantarum group Lactobacilli becomes dominant and affects lipid metabolism by altering bile acid signaling.

Reduced densities of the invasive wasp, Vespula vulgaris (Hymenoptera: Vespidae), did not alter the invertebrate community composition of Nothofagus forests in New Zealand.

PubMed

Duthie, Catherine; Lester, Philip J

2013-04-01

Invasive common wasps (Vespula vulgaris L.) are predators of invertebrates in Nothofagus forests of New Zealand. We reduced wasp densities by poisoning in three sites over three y. We predicted an increase in the number of invertebrates and a change in the community composition in sites where wasps were poisoned (wasps removed) relative to nearby sites where wasps were not poisoned (wasps maintained). Wasp densities were significantly reduced by an average of 58.9% by poisoning. Despite this reduction in wasp densities, native bush ants (Prolasius advenus Forel) were the only taxa that was significantly influenced by wasp removal. However, contrary to our predictions there were more ants caught in pitfall traps where wasps were maintained. We believe that the higher abundance of these ants is probably because of the scarcity of honeydew in wasp-maintained sites and compensatory foraging by ants in these areas. Otherwise, our results indicated no significant effects of reduced wasp densities on the total number of invertebrates, or the number of invertebrate families, observed in pitfall or Malaise traps. An analysis of community composition (permutational multivariate analysis of variance) also indicated no significant difference between wasp-removed or wasp-maintained communities. The most parsimonious explanation for our results is that although we significantly reduced wasp numbers, we may not have reduced numbers sufficiently or for a sufficiently long period, to see a change or recovery in the community.

Grassland Fire and Cattle Grazing Regulate Reptile and Amphibian Assembly Among Patches

NASA Astrophysics Data System (ADS)

Larson, Danelle M.

2014-12-01

Fire and grazing are common management schemes of grasslands globally and are potential drivers of reptilian and amphibian (herpetofauna) metacommunity dynamics. Few studies have assessed the impacts of fire and cattle grazing on herpetofauna assemblages in grasslands. A patch-burn grazing study at Osage Prairie, MO, USA in 2011-2012 created landscape patches with treatments of grazing, fire, and such legacies. Response variables were measured before and after the application of treatments, and I used robust-design occupancy modeling to estimate patch occupancy and detection rate within patches, and recolonization and extinction (i.e., dispersal) across patches. I conducted redundancy analysis and a permuted multivariate analysis of variance to determine if patch type and the associated environmental factors explained herpetofauna assemblage. Estimates for reptiles indicate that occupancy was seasonally constant in Control patches ( ψ ~ 0.5), but declined to ψ ~ 0.15 in patches following the applications of fire and grazing. Local extinctions for reptiles were higher in patches with fire or light grazing ( ɛ ~ 0.7) compared to the controls. For the riparian herpetofaunal community, patch type and grass height were important predictors of abundance; further, the turtles, lizards, snakes, and adult amphibians used different patch types. The aquatic amphibian community was predicted by watershed and in-stream characteristics, irrespective of fire or grazing. The varying responses from taxonomic groups demonstrate habitat partitioning across multiple patch types undergoing fire, cattle grazing, and legacy effects. Prairies will need an array of patch types to accommodate multiple herpetofauna species.

Introduction to Permutation and Resampling-Based Hypothesis Tests

ERIC Educational Resources Information Center

LaFleur, Bonnie J.; Greevy, Robert A.

2009-01-01

A resampling-based method of inference--permutation tests--is often used when distributional assumptions are questionable or unmet. Not only are these methods useful for obvious departures from parametric assumptions (e.g., normality) and small sample sizes, but they are also more robust than their parametric counterparts in the presences of…

Explorations in Statistics: Permutation Methods

ERIC Educational Resources Information Center

Curran-Everett, Douglas

2012-01-01

Learning about statistics is a lot like learning about science: the learning is more meaningful if you can actively explore. This eighth installment of "Explorations in Statistics" explores permutation methods, empiric procedures we can use to assess an experimental result--to test a null hypothesis--when we are reluctant to trust statistical…

STRUCTURAL AND FUNCTIONAL CONSEQUENCES OF CIRCULAR PERMUTATION ON THE ACTIVE SITE OF OLD YELLOW ENZYME.

PubMed

Daugherty, Ashley B; Horton, John R; Cheng, Xiaodong; Lutz, Stefan

2015-02-06

Circular permutation of the NADPH-dependent oxidoreductase Old Yellow Enzyme from Saccharomyces pastorianus (OYE1) can significantly enhance the enzyme's catalytic performance. Termini relocation into four regions of the protein (sectors I-IV) near the active site has proven effective in altering enzyme function. To better understand the structural consequences and rationalize the observed functional gains in these OYE1 variants, we selected representatives from sectors I-III for further characterization by biophysical methods and X-ray crystallography. These investigations not only show trends in enzyme stability and quaternary structure as a function of termini location, but also provide a possible explanation for the catalytic gains in our top-performing OYE variant (new N-terminus at residue 303; sector III). Crystallographic analysis indicates that termini relocation into sector III affects the loop β6 region (amino acid positions: 290-310) of OYE1 which forms a lid over the active site. Peptide backbone cleavage greatly enhances local flexibility, effectively converting the loop into a tether and consequently increasing the environmental exposure of the active site. Interestingly, such active site remodeling does not negatively impact the enzyme's activity and stereoselectivity, nor does it perturb the conformation of other key active site residues with the exception of Y375. These observations were confirmed in truncation experiments, deleting all residues of the loop β6 region in our OYE variant. Intrigued by the finding that circular permutation leaves most of the key catalytic residues unchanged, we also tested OYE permutants for possible additive or synergistic effects of amino acid substitutions. Distinct functional changes in these OYE variants were detected upon mutations at W116, known in native OYE1 to cause inversion of diastereo-selectivity for ( S )-carvone reduction. Our findings demonstrate the contribution of loop β6 toward determining the stereoselectivity of OYE1, an important insight for future OYE engineering efforts.

Structural and Functional Consequences of Circular Permutation on the Active Site of Old Yellow Enzyme

DOE PAGES

Daugherty, Ashley B.; Horton, John R.; Cheng, Xiaodong; ...

2014-12-09

Circular permutation of the NADPH-dependent oxidoreductase Old Yellow Enzyme from Saccharomyces pastorianus (OYE1) can significantly enhance the enzyme’s catalytic performance. Termini relocation into four regions of the protein (sectors I–IV) near the active site has proven effective in altering enzyme function. To better understand the structural consequences and rationalize the observed functional gains in these OYE1 variants, we selected representatives from sectors I–III for further characterization by biophysical methods and X-ray crystallography. These investigations not only show trends in enzyme stability and quaternary structure as a function of termini location but also provide a possible explanation for the catalytic gainsmore » in our top-performing OYE variant (new N-terminus at residue 303; sector III). Crystallographic analysis indicates that termini relocation into sector III affects the loop β6 region (amino acid positions: 290–310) of OYE1, which forms a lid over the active site. Peptide backbone cleavage greatly enhances local flexibility, effectively converting the loop into a tether and consequently increasing the environmental exposure of the active site. Interestingly, such an active site remodeling does not negatively impact the enzyme’s activity and stereoselectivity; neither does it perturb the conformation of other key active site residues with the exception of Y375. These observations were confirmed in truncation experiments, deleting all residues of the loop β6 region in our OYE variant. Intrigued by the finding that circular permutation leaves most of the key catalytic residues unchanged, we also tested OYE permutants for possible additive or synergistic effects of amino acid substitutions. Distinct functional changes in these OYE variants were detected upon mutations at W116, known in native OYE1 to cause inversion of diastereoselectivity for (S)-carvone reduction. In conclusion, our findings demonstrate the contribution of loop β6 toward determining the stereoselectivity of OYE1, an important insight for future OYE engineering efforts.« less

Overcoming the effects of false positives and threshold bias in graph theoretical analyses of neuroimaging data.

PubMed

Drakesmith, M; Caeyenberghs, K; Dutt, A; Lewis, G; David, A S; Jones, D K

2015-09-01

Graph theory (GT) is a powerful framework for quantifying topological features of neuroimaging-derived functional and structural networks. However, false positive (FP) connections arise frequently and influence the inferred topology of networks. Thresholding is often used to overcome this problem, but an appropriate threshold often relies on a priori assumptions, which will alter inferred network topologies. Four common network metrics (global efficiency, mean clustering coefficient, mean betweenness and smallworldness) were tested using a model tractography dataset. It was found that all four network metrics were significantly affected even by just one FP. Results also show that thresholding effectively dampens the impact of FPs, but at the expense of adding significant bias to network metrics. In a larger number (n=248) of tractography datasets, statistics were computed across random group permutations for a range of thresholds, revealing that statistics for network metrics varied significantly more than for non-network metrics (i.e., number of streamlines and number of edges). Varying degrees of network atrophy were introduced artificially to half the datasets, to test sensitivity to genuine group differences. For some network metrics, this atrophy was detected as significant (p<0.05, determined using permutation testing) only across a limited range of thresholds. We propose a multi-threshold permutation correction (MTPC) method, based on the cluster-enhanced permutation correction approach, to identify sustained significant effects across clusters of thresholds. This approach minimises requirements to determine a single threshold a priori. We demonstrate improved sensitivity of MTPC-corrected metrics to genuine group effects compared to an existing approach and demonstrate the use of MTPC on a previously published network analysis of tractography data derived from a clinical population. In conclusion, we show that there are large biases and instability induced by thresholding, making statistical comparisons of network metrics difficult. However, by testing for effects across multiple thresholds using MTPC, true group differences can be robustly identified. Copyright © 2015. Published by Elsevier Inc.

Novel Image Encryption Scheme Based on Chebyshev Polynomial and Duffing Map

PubMed Central

2014-01-01

We present a novel image encryption algorithm using Chebyshev polynomial based on permutation and substitution and Duffing map based on substitution. Comprehensive security analysis has been performed on the designed scheme using key space analysis, visual testing, histogram analysis, information entropy calculation, correlation coefficient analysis, differential analysis, key sensitivity test, and speed test. The study demonstrates that the proposed image encryption algorithm shows advantages of more than 10113 key space and desirable level of security based on the good statistical results and theoretical arguments. PMID:25143970

Comprehensive microbiome analysis of tonsillar crypts in IgA nephropathy.

PubMed

Watanabe, Hirofumi; Goto, Shin; Mori, Hiroshi; Higashi, Koichi; Hosomichi, Kazuyoshi; Aizawa, Naotaka; Takahashi, Nao; Tsuchida, Masafumi; Suzuki, Yusuke; Yamada, Takuji; Horii, Arata; Inoue, Ituro; Kurokawa, Ken; Narita, Ichiei

2017-12-01

Immunoglobulin A nephropathy (IgAN) is the most prevalent primary chronic glomerular disease, in which the mucosal immune response elicited particularly in the tonsils or intestine has been estimated to be involved in the development of the disease. To explore the relationship between IgAN and bacterial flora in the tonsils, we conducted a comprehensive microbiome analysis. We enrolled 48 IgAN patients, 21 recurrent tonsillitis (RT) patients without urine abnormalities and 30 children with tonsillar hyperplasia (TH) who had undergone tonsillectomy previously. Genomic DNA from tonsillar crypts of each patient was extracted, and V4 regions of the 16S ribosomal RNA gene were amplified and analysed using a high-throughput multiplexed sequencing approach. Differences in genus composition among the three study groups were statistically analysed by permutational multivariate analysis of variance and visualized by principal component analysis (PCA). Substantial diversity in bacterial composition was detected in each sample. Prevotella spp., Fusobacterium spp., Sphingomonas spp. and Treponema spp. were predominant in IgAN patients. The percentage of abundance of Prevotella spp., Haemophilus spp., Porphyromonas spp. and Treponema spp. in IgAN patients was significantly different from that in TH patients. However, there was no significant difference in the percentage of abundance of any bacterial genus between IgAN and RT patients. PCA did not distinguish IgAN from RT, although it discriminated TH. No significant differences in microbiome composition among the groups of IgAN patients according to clinicopathological parameters were observed. Similar patterns of bacteria are present in tonsillar crypts of both IgAN and RT patients, suggesting that the host response to these bacteria might be important in the development of IgAN. © The Author 2016. Published by Oxford University Press on behalf of ERA-EDTA. All rights reserved.

NASA Thesaurus. Volume 2: Access vocabulary

NASA Technical Reports Server (NTRS)

1976-01-01

The NASA Thesaurus -- Volume 2, Access Vocabulary -- contains an alphabetical listing of all Thesaurus terms (postable and nonpostable) and permutations of all multiword and pseudo-multiword terms. Also included are Other Words (non-Thesaurus terms) consisting of abbreviations, chemical symbols, etc. The permutations and Other Words provide 'access' to the appropriate postable entries in the Thesaurus.

A Permutation Test for Correlated Errors in Adjacent Questionnaire Items

ERIC Educational Resources Information Center

Hildreth, Laura A.; Genschel, Ulrike; Lorenz, Frederick O.; Lesser, Virginia M.

2013-01-01

Response patterns are of importance to survey researchers because of the insight they provide into the thought processes respondents use to answer survey questions. In this article we propose the use of structural equation modeling to examine response patterns and develop a permutation test to quantify the likelihood of observing a specific…

The Parity Theorem Shuffle

ERIC Educational Resources Information Center

Smith, Michael D.

2016-01-01

The Parity Theorem states that any permutation can be written as a product of transpositions, but no permutation can be written as a product of both an even number and an odd number of transpositions. Most proofs of the Parity Theorem take several pages of mathematical formalism to complete. This article presents an alternative but equivalent…

Sorting signed permutations by inversions in O(nlogn) time.

PubMed

Swenson, Krister M; Rajan, Vaibhav; Lin, Yu; Moret, Bernard M E

2010-03-01

The study of genomic inversions (or reversals) has been a mainstay of computational genomics for nearly 20 years. After the initial breakthrough of Hannenhalli and Pevzner, who gave the first polynomial-time algorithm for sorting signed permutations by inversions, improved algorithms have been designed, culminating with an optimal linear-time algorithm for computing the inversion distance and a subquadratic algorithm for providing a shortest sequence of inversions--also known as sorting by inversions. Remaining open was the question of whether sorting by inversions could be done in O(nlogn) time. In this article, we present a qualified answer to this question, by providing two new sorting algorithms, a simple and fast randomized algorithm and a deterministic refinement. The deterministic algorithm runs in time O(nlogn + kn), where k is a data-dependent parameter. We provide the results of extensive experiments showing that both the average and the standard deviation for k are small constants, independent of the size of the permutation. We conclude (but do not prove) that almost all signed permutations can be sorted by inversions in O(nlogn) time.

Revisiting the European sovereign bonds with a permutation-information-theory approach

NASA Astrophysics Data System (ADS)

Fernández Bariviera, Aurelio; Zunino, Luciano; Guercio, María Belén; Martinez, Lisana B.; Rosso, Osvaldo A.

2013-12-01

In this paper we study the evolution of the informational efficiency in its weak form for seventeen European sovereign bonds time series. We aim to assess the impact of two specific economic situations in the hypothetical random behavior of these time series: the establishment of a common currency and a wide and deep financial crisis. In order to evaluate the informational efficiency we use permutation quantifiers derived from information theory. Specifically, time series are ranked according to two metrics that measure the intrinsic structure of their correlations: permutation entropy and permutation statistical complexity. These measures provide the rectangular coordinates of the complexity-entropy causality plane; the planar location of the time series in this representation space reveals the degree of informational efficiency. According to our results, the currency union contributed to homogenize the stochastic characteristics of the time series and produced synchronization in the random behavior of them. Additionally, the 2008 financial crisis uncovered differences within the apparently homogeneous European sovereign markets and revealed country-specific characteristics that were partially hidden during the monetary union heyday.

Healing and Conversion in New Religious Movements in Africa: Elements of an Indigenous Epistemology.

ERIC Educational Resources Information Center

Sanneh, Lamin

In this analysis of healing and conversion as two of the most notable and persistent traits of the new religious movements in Africa, healing is described as an indigenous religious category within the context of conversion as a modern permutation of African religion. Religious conversion is most strikingly represented in societies where the…

Symmetric encryption algorithms using chaotic and non-chaotic generators: A review

PubMed Central

Radwan, Ahmed G.; AbdElHaleem, Sherif H.; Abd-El-Hafiz, Salwa K.

2015-01-01

This paper summarizes the symmetric image encryption results of 27 different algorithms, which include substitution-only, permutation-only or both phases. The cores of these algorithms are based on several discrete chaotic maps (Arnold’s cat map and a combination of three generalized maps), one continuous chaotic system (Lorenz) and two non-chaotic generators (fractals and chess-based algorithms). Each algorithm has been analyzed by the correlation coefficients between pixels (horizontal, vertical and diagonal), differential attack measures, Mean Square Error (MSE), entropy, sensitivity analyses and the 15 standard tests of the National Institute of Standards and Technology (NIST) SP-800-22 statistical suite. The analyzed algorithms include a set of new image encryption algorithms based on non-chaotic generators, either using substitution only (using fractals) and permutation only (chess-based) or both. Moreover, two different permutation scenarios are presented where the permutation-phase has or does not have a relationship with the input image through an ON/OFF switch. Different encryption-key lengths and complexities are provided from short to long key to persist brute-force attacks. In addition, sensitivities of those different techniques to a one bit change in the input parameters of the substitution key as well as the permutation key are assessed. Finally, a comparative discussion of this work versus many recent research with respect to the used generators, type of encryption, and analyses is presented to highlight the strengths and added contribution of this paper. PMID:26966561

Development of isothermal-isobaric replica-permutation method for molecular dynamics and Monte Carlo simulations and its application to reveal temperature and pressure dependence of folded, misfolded, and unfolded states of chignolin

NASA Astrophysics Data System (ADS)

Yamauchi, Masataka; Okumura, Hisashi

2017-11-01

We developed a two-dimensional replica-permutation molecular dynamics method in the isothermal-isobaric ensemble. The replica-permutation method is a better alternative to the replica-exchange method. It was originally developed in the canonical ensemble. This method employs the Suwa-Todo algorithm, instead of the Metropolis algorithm, to perform permutations of temperatures and pressures among more than two replicas so that the rejection ratio can be minimized. We showed that the isothermal-isobaric replica-permutation method performs better sampling efficiency than the isothermal-isobaric replica-exchange method and infinite swapping method. We applied this method to a β-hairpin mini protein, chignolin. In this simulation, we observed not only the folded state but also the misfolded state. We calculated the temperature and pressure dependence of the fractions on the folded, misfolded, and unfolded states. Differences in partial molar enthalpy, internal energy, entropy, partial molar volume, and heat capacity were also determined and agreed well with experimental data. We observed a new phenomenon that misfolded chignolin becomes more stable under high-pressure conditions. We also revealed this mechanism of the stability as follows: TYR2 and TRP9 side chains cover the hydrogen bonds that form a β-hairpin structure. The hydrogen bonds are protected from the water molecules that approach the protein as the pressure increases.

EXPLICIT SYMPLECTIC-LIKE INTEGRATORS WITH MIDPOINT PERMUTATIONS FOR SPINNING COMPACT BINARIES

DOE Office of Scientific and Technical Information (OSTI.GOV)

Luo, Junjie; Wu, Xin; Huang, Guoqing

2017-01-01

We refine the recently developed fourth-order extended phase space explicit symplectic-like methods for inseparable Hamiltonians using Yoshida’s triple product combined with a midpoint permuted map. The midpoint between the original variables and their corresponding extended variables at every integration step is readjusted as the initial values of the original variables and their corresponding extended ones at the next step integration. The triple-product construction is apparently superior to the composition of two triple products in computational efficiency. Above all, the new midpoint permutations are more effective in restraining the equality of the original variables and their corresponding extended ones at each integration step thanmore » the existing sequent permutations of momenta and coordinates. As a result, our new construction shares the benefit of implicit symplectic integrators in the conservation of the second post-Newtonian Hamiltonian of spinning compact binaries. Especially for the chaotic case, it can work well, but the existing sequent permuted algorithm cannot. When dissipative effects from the gravitational radiation reaction are included, the new symplectic-like method has a secular drift in the energy error of the dissipative system for the orbits that are regular in the absence of radiation, as an implicit symplectic integrator does. In spite of this, it is superior to the same-order implicit symplectic integrator in accuracy and efficiency. The new method is particularly useful in discussing the long-term evolution of inseparable Hamiltonian problems.« less

A studentized permutation test for three-arm trials in the 'gold standard' design.

PubMed

Mütze, Tobias; Konietschke, Frank; Munk, Axel; Friede, Tim

2017-03-15

The 'gold standard' design for three-arm trials refers to trials with an active control and a placebo control in addition to the experimental treatment group. This trial design is recommended when being ethically justifiable and it allows the simultaneous comparison of experimental treatment, active control, and placebo. Parametric testing methods have been studied plentifully over the past years. However, these methods often tend to be liberal or conservative when distributional assumptions are not met particularly with small sample sizes. In this article, we introduce a studentized permutation test for testing non-inferiority and superiority of the experimental treatment compared with the active control in three-arm trials in the 'gold standard' design. The performance of the studentized permutation test for finite sample sizes is assessed in a Monte Carlo simulation study under various parameter constellations. Emphasis is put on whether the studentized permutation test meets the target significance level. For comparison purposes, commonly used Wald-type tests, which do not make any distributional assumptions, are included in the simulation study. The simulation study shows that the presented studentized permutation test for assessing non-inferiority in three-arm trials in the 'gold standard' design outperforms its competitors, for instance the test based on a quasi-Poisson model, for count data. The methods discussed in this paper are implemented in the R package ThreeArmedTrials which is available on the comprehensive R archive network (CRAN). Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Statistical validation of normal tissue complication probability models.

PubMed

Xu, Cheng-Jian; van der Schaaf, Arjen; Van't Veld, Aart A; Langendijk, Johannes A; Schilstra, Cornelis

2012-09-01

To investigate the applicability and value of double cross-validation and permutation tests as established statistical approaches in the validation of normal tissue complication probability (NTCP) models. A penalized regression method, LASSO (least absolute shrinkage and selection operator), was used to build NTCP models for xerostomia after radiation therapy treatment of head-and-neck cancer. Model assessment was based on the likelihood function and the area under the receiver operating characteristic curve. Repeated double cross-validation showed the uncertainty and instability of the NTCP models and indicated that the statistical significance of model performance can be obtained by permutation testing. Repeated double cross-validation and permutation tests are recommended to validate NTCP models before clinical use. Copyright © 2012 Elsevier Inc. All rights reserved.

Permutation testing of orthogonal factorial effects in a language-processing experiment using fMRI.

PubMed

Suckling, John; Davis, Matthew H; Ooi, Cinly; Wink, Alle Meije; Fadili, Jalal; Salvador, Raymond; Welchew, David; Sendur, Levent; Maxim, Vochita; Bullmore, Edward T

2006-05-01

The block-paradigm of the Functional Image Analysis Contest (FIAC) dataset was analysed with the Brain Activation and Morphological Mapping software. Permutation methods in the wavelet domain were used for inference on cluster-based test statistics of orthogonal contrasts relevant to the factorial design of the study, namely: the average response across all active blocks, the main effect of speaker, the main effect of sentence, and the interaction between sentence and speaker. Extensive activation was seen with all these contrasts. In particular, different vs. same-speaker blocks produced elevated activation in bilateral regions of the superior temporal lobe and repetition suppression for linguistic materials (same vs. different-sentence blocks) in left inferior frontal regions. These are regions previously reported in the literature. Additional regions were detected in this study, perhaps due to the enhanced sensitivity of the methodology. Within-block sentence suppression was tested post-hoc by regression of an exponential decay model onto the extracted time series from the left inferior frontal gyrus, but no strong evidence of such an effect was found. The significance levels set for the activation maps are P-values at which we expect <1 false-positive cluster per image. Nominal type I error control was verified by empirical testing of a test statistic corresponding to a randomly ordered design matrix. The small size of the BOLD effect necessitates sensitive methods of detection of brain activation. Permutation methods permit the necessary flexibility to develop novel test statistics to meet this challenge.

The complexity of gene expression dynamics revealed by permutation entropy

PubMed Central

2010-01-01

Background High complexity is considered a hallmark of living systems. Here we investigate the complexity of temporal gene expression patterns using the concept of Permutation Entropy (PE) first introduced in dynamical systems theory. The analysis of gene expression data has so far focused primarily on the identification of differentially expressed genes, or on the elucidation of pathway and regulatory relationships. We aim to study gene expression time series data from the viewpoint of complexity. Results Applying the PE complexity metric to abiotic stress response time series data in Arabidopsis thaliana, genes involved in stress response and signaling were found to be associated with the highest complexity not only under stress, but surprisingly, also under reference, non-stress conditions. Genes with house-keeping functions exhibited lower PE complexity. Compared to reference conditions, the PE of temporal gene expression patterns generally increased upon stress exposure. High-complexity genes were found to have longer upstream intergenic regions and more cis-regulatory motifs in their promoter regions indicative of a more complex regulatory apparatus needed to orchestrate their expression, and to be associated with higher correlation network connectivity degree. Arabidopsis genes also present in other plant species were observed to exhibit decreased PE complexity compared to Arabidopsis specific genes. Conclusions We show that Permutation Entropy is a simple yet robust and powerful approach to identify temporal gene expression profiles of varying complexity that is equally applicable to other types of molecular profile data. PMID:21176199

Extending Differential Fault Analysis to Dynamic S-Box Advanced Encryption Standard Implementations

DTIC Science & Technology

2014-09-18

entropy . At the same time, researchers strive to enhance AES and mitigate these growing threats. This paper researches the extension of existing...the algorithm or use side channels to reduce entropy , such as Differential Fault Analysis (DFA). At the same time, continuing research strives to...the state matrix. The S-box is an 8-bit 16x16 table built from an affine transformation on multiplicative inverses which guarantees full permutation (S

Application of microarray analysis on computer cluster and cloud platforms.

PubMed

Bernau, C; Boulesteix, A-L; Knaus, J

2013-01-01

Analysis of recent high-dimensional biological data tends to be computationally intensive as many common approaches such as resampling or permutation tests require the basic statistical analysis to be repeated many times. A crucial advantage of these methods is that they can be easily parallelized due to the computational independence of the resampling or permutation iterations, which has induced many statistics departments to establish their own computer clusters. An alternative is to rent computing resources in the cloud, e.g. at Amazon Web Services. In this article we analyze whether a selection of statistical projects, recently implemented at our department, can be efficiently realized on these cloud resources. Moreover, we illustrate an opportunity to combine computer cluster and cloud resources. In order to compare the efficiency of computer cluster and cloud implementations and their respective parallelizations we use microarray analysis procedures and compare their runtimes on the different platforms. Amazon Web Services provide various instance types which meet the particular needs of the different statistical projects we analyzed in this paper. Moreover, the network capacity is sufficient and the parallelization is comparable in efficiency to standard computer cluster implementations. Our results suggest that many statistical projects can be efficiently realized on cloud resources. It is important to mention, however, that workflows can change substantially as a result of a shift from computer cluster to cloud computing.

Efficient and Robust Signal Approximations

DTIC Science & Technology

2009-05-01

otherwise. Remark. Permutation matrices are both orthogonal and doubly- stochastic [62]. We will now show how to further simplify the Robust Coding...reporting burden for the collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching...Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 Keywords: signal processing, image compression, independent component analysis , sparse

Four-Year-Old Cantonese-Speaking Children's Online Processing of Relative Clauses: A Permutation Analysis

ERIC Educational Resources Information Center

Chan, Angel; Yang, Wenchun; Chang, Franklin; Kidd, Evan

2018-01-01

We report on an eye-tracking study that investigated four-year-old Cantonese-speaking children's online processing of subject and object relative clauses (RCs). Children's eye-movements were recorded as they listened to RC structures identifying a unique referent (e.g. "Can you pick up the horse that pushed the pig?"). Two RC types,…

Algorithms and programming tools for image processing on the MPP:3

NASA Technical Reports Server (NTRS)

Reeves, Anthony P.

1987-01-01

This is the third and final report on the work done for NASA Grant 5-403 on Algorithms and Programming Tools for Image Processing on the MPP:3. All the work done for this grant is summarized in the introduction. Work done since August 1986 is reported in detail. Research for this grant falls under the following headings: (1) fundamental algorithms for the MPP; (2) programming utilities for the MPP; (3) the Parallel Pascal Development System; and (4) performance analysis. In this report, the results of two efforts are reported: region growing, and performance analysis of important characteristic algorithms. In each case, timing results from MPP implementations are included. A paper is included in which parallel algorithms for region growing on the MPP is discussed. These algorithms permit different sized regions to be merged in parallel. Details on the implementation and peformance of several important MPP algorithms are given. These include a number of standard permutations, the FFT, convolution, arbitrary data mappings, image warping, and pyramid operations, all of which have been implemented on the MPP. The permutation and image warping functions have been included in the standard development system library.

EARLY CHILDHOOD INVESTMENTS SUBSTANTIALLY BOOST ADULT HEALTH

PubMed Central

Campbell, Frances; Conti, Gabriella; Heckman, James J.; Moon, Seong Hyeok; Pinto, Rodrigo; Pungello, Elizabeth; Pan, Yi

2014-01-01

High-quality early childhood programs have been shown to have substantial benefits in reducing crime, raising earnings, and promoting education. Much less is known about their benefits for adult health. We report the long-term health impacts of one of the oldest and most heavily cited early childhood interventions with long-term follow-up evaluated by the method of randomization: the Carolina Abecedarian Project (ABC). Using recently collected biomedical data, we find that disadvantaged children randomly assigned to treatment have significantly lower prevalence of risk factors for cardiovascular and metabolic diseases in their mid-30s. The evidence is especially strong for males. The mean systolic blood pressure among the control males is 143, while only 126 among the treated. One in four males in the control group is affected by metabolic syndrome, while none in the treatment group is. To reach these conclusions, we address several statistical challenges. We use exact permutation tests to account for small sample sizes and conduct a parallel bootstrap confidence interval analysis to confirm the permutation analysis. We adjust inference to account for the multiple hypotheses tested and for nonrandom attrition. Our evidence shows the potential of early life interventions for preventing disease and promoting health. PMID:24675955

Harnessing Multivariate Statistics for Ellipsoidal Data in Structural Geology

NASA Astrophysics Data System (ADS)

Roberts, N.; Davis, J. R.; Titus, S.; Tikoff, B.

2015-12-01

Most structural geology articles do not state significance levels, report confidence intervals, or perform regressions to find trends. This is, in part, because structural data tend to include directions, orientations, ellipsoids, and tensors, which are not treatable by elementary statistics. We describe a full procedural methodology for the statistical treatment of ellipsoidal data. We use a reconstructed dataset of deformed ooids in Maryland from Cloos (1947) to illustrate the process. Normalized ellipsoids have five degrees of freedom and can be represented by a second order tensor. This tensor can be permuted into a five dimensional vector that belongs to a vector space and can be treated with standard multivariate statistics. Cloos made several claims about the distribution of deformation in the South Mountain fold, Maryland, and we reexamine two particular claims using hypothesis testing: 1) octahedral shear strain increases towards the axial plane of the fold; 2) finite strain orientation varies systematically along the trend of the axial trace as it bends with the Appalachian orogen. We then test the null hypothesis that the southern segment of South Mountain is the same as the northern segment. This test illustrates the application of ellipsoidal statistics, which combine both orientation and shape. We report confidence intervals for each test, and graphically display our results with novel plots. This poster illustrates the importance of statistics in structural geology, especially when working with noisy or small datasets.

Enteral Tube Feeding Alters the Oral Indigenous Microbiota in Elderly Adults ▿ †

PubMed Central

Takeshita, Toru; Yasui, Masaki; Tomioka, Mikiko; Nakano, Yoshio; Shimazaki, Yoshihiro; Yamashita, Yoshihisa

2011-01-01

Enteral tube feeding is widely used to maintain nutrition for elderly adults with eating difficulties, but its long-term use alters the environment of the oral ecosystem. This study characterized the tongue microbiota of tube-fed elderly adults by analyzing the 16S rRNA gene. The terminal restriction fragment length polymorphism (T-RFLP) profiles of 44 tube-fed subjects were compared with those of 54 subjects fed orally (average age, 86.4 ± 6.9 years). Bar-coded pyrosequencing data were also obtained for a subset of the subjects from each group (15 tube-fed subjects and 16 subjects fed orally). The T-RFLP profiles demonstrated that the microbiota of the tube-fed subjects was distinct from that of the subjects fed orally (permutational multivariate analysis of variance [perMANOVA], P < 0.001). The pyrosequencing data revealed that 22 bacterial genera, including Corynebacterium, Peptostreptococcus, and Fusobacterium, were significantly more predominant in tube-fed subjects, whereas the dominant genera in the subjects fed orally, such as Streptococcus and Veillonella, were present in much lower proportions. Opportunistic pathogens rarely detected in the normal oral microbiota, such as Corynebacterium striatum and Streptococcus agalactiae, were often found in high proportions in tube-fed subjects. The oral indigenous microbiota is disrupted by the use of enteral feeding, allowing health-threatening bacteria to thrive. PMID:21821752

Use of gene expression data to determine effects on gonad phenotype in Japanese medaka after exposure to trenbolone or estradiol.

PubMed

Flynn, Kevin; Swintek, Joe; Johnson, Rodney

2013-06-01

Various aquatic bioassays using one of several fish species have been developed or are in the process of being developed by organizations like the US Environmental Protection Agency and the Office of Economic Cooperation and Development for testing potential endocrine-disrupting chemicals (EDCs). Often, these involve assessment of the gonad phenotype of individuals as a key endpoint that is inputted into a risk or hazard assessment. Typically, gonad phenotype is determined histologically, which involves specialized and time-consuming techniques. The methods detailed here utilize an entirely different methodology, reverse-transcription quantitative polymerase chain reaction, to determine the relative expression levels of 4 genes after exposure to either 17β-estradiol or 17β-trenbolone and, by extension, the effects of EDCs on the phenotypic status of the gonad. The 4 genes quantified, Sox9b, protamine, Fig1α, and ZPC1, are all involved in gonad development and maintenance in Japanese medaka (Oryzias latipes); these data were then inputted into a permutational multivariate analysis of variance to determine whether significant differences exist between treatment groups. This information in conjunction with the sexual genotype, which can be determined in medaka, can be used to determine adverse effects of exposure to EDCs in a similar fashion to the histologically determined gonad phenotype. Copyright © 2013 SETAC.

Plant-facilitated effects of exotic earthworm Pontoscolex corethrurus on the soil carbon and nitrogen dynamics and soil microbial community in a subtropical field ecosystem.

PubMed

Wu, Jianping; Zhang, Weixin; Shao, Yuanhu; Fu, Shenglei

2017-11-01

Earthworms and plants greatly affect belowground properties; however, their combined effects are more attractive based on the ecosystem scale in the field condition. To address this point, we manipulated earthworms (exotic endogeic species Pontoscolex corethrurus ) and plants (living plants [native tree species Evodia lepta ] and artificial plants) to investigate their combined effects on soil microorganisms, soil nutrients, and soil respiration in a subtropical forest. The manipulation of artificial plants aimed to simulate the physical effects of plants (e.g., shading and interception of water) such that the biological effects of plants could be evaluated separately. We found that relative to the controls, living plants but not artificial plants significantly increased the ratio of fungal to bacterial phospholipid fatty acids (PLFAs) and fungal PLFAs. Furthermore, earthworms plus living plants significantly increased the soil respiration and decreased the soil NH 4 + -N, which indicates that the earthworm effects on the associated carbon, and nitrogen processes were greatly affected by living plants. The permutational multivariate analysis of variance results also indicated that living plants but not earthworms or artificial plants significantly changed the soil microbial community. Our results suggest that the effects of plants on soil microbes and associated soil properties in this study were largely explained by their biological rather than their physical effects.

NASA thesaurus. Volume 2: Access vocabulary

NASA Technical Reports Server (NTRS)

1985-01-01

The Access Vocabulary, which is essentially a permuted index, provides access to any word or number in authorized postable and nonpostable terms. Additional entries include postable and nonpostable terms, other word entries, and pseudo-multiword terms that are permutations of words that contain words within words. The Access Vocabulary contains 40,738 entries that give increased access to the hierarchies in Volume 1 - Hierarchical Listing.

NASA Thesaurus. Volume 2: Access vocabulary

NASA Technical Reports Server (NTRS)

1982-01-01

The Access Vocabulary, which is essentially a permuted index, provides access to any word or number in authorized postable and nonpostable terms. Additional entries include postable and nonpostable terms, other word entries, and pseudo-multiword terms that are permutations of words that contain words within words. The Access Vocabulary contains, 40,661 entries that give increased access to he hierarchies in Volume 1 - Hierarchical Listing.

Optimal control of hybrid qubits: Implementing the quantum permutation algorithm

NASA Astrophysics Data System (ADS)

Rivera-Ruiz, C. M.; de Lima, E. F.; Fanchini, F. F.; Lopez-Richard, V.; Castelano, L. K.

2018-03-01

The optimal quantum control theory is employed to determine electric pulses capable of producing quantum gates with a fidelity higher than 0.9997, when noise is not taken into account. Particularly, these quantum gates were chosen to perform the permutation algorithm in hybrid qubits in double quantum dots (DQDs). The permutation algorithm is an oracle based quantum algorithm that solves the problem of the permutation parity faster than a classical algorithm without the necessity of entanglement between particles. The only requirement for achieving the speedup is the use of a one-particle quantum system with at least three levels. The high fidelity found in our results is closely related to the quantum speed limit, which is a measure of how fast a quantum state can be manipulated. Furthermore, we model charge noise by considering an average over the optimal field centered at different values of the reference detuning, which follows a Gaussian distribution. When the Gaussian spread is of the order of 5 μ eV (10% of the correct value), the fidelity is still higher than 0.95. Our scheme also can be used for the practical realization of different quantum algorithms in DQDs.

Weighted multiscale Rényi permutation entropy of nonlinear time series

NASA Astrophysics Data System (ADS)

Chen, Shijian; Shang, Pengjian; Wu, Yue

2018-04-01

In this paper, based on Rényi permutation entropy (RPE), which has been recently suggested as a relative measure of complexity in nonlinear systems, we propose multiscale Rényi permutation entropy (MRPE) and weighted multiscale Rényi permutation entropy (WMRPE) to quantify the complexity of nonlinear time series over multiple time scales. First, we apply MPRE and WMPRE to the synthetic data and make a comparison of modified methods and RPE. Meanwhile, the influence of the change of parameters is discussed. Besides, we interpret the necessity of considering not only multiscale but also weight by taking the amplitude into account. Then MRPE and WMRPE methods are employed to the closing prices of financial stock markets from different areas. By observing the curves of WMRPE and analyzing the common statistics, stock markets are divided into 4 groups: (1) DJI, S&P500, and HSI, (2) NASDAQ and FTSE100, (3) DAX40 and CAC40, and (4) ShangZheng and ShenCheng. Results show that the standard deviations of weighted methods are smaller, showing WMRPE is able to ensure the results more robust. Besides, WMPRE can provide abundant dynamical properties of complex systems, and demonstrate the intrinsic mechanism.

PsiQuaSP-A library for efficient computation of symmetric open quantum systems.

PubMed

Gegg, Michael; Richter, Marten

2017-11-24

In a recent publication we showed that permutation symmetry reduces the numerical complexity of Lindblad quantum master equations for identical multi-level systems from exponential to polynomial scaling. This is important for open system dynamics including realistic system bath interactions and dephasing in, for instance, the Dicke model, multi-Λ system setups etc. Here we present an object-oriented C++ library that allows to setup and solve arbitrary quantum optical Lindblad master equations, especially those that are permutationally symmetric in the multi-level systems. PsiQuaSP (Permutation symmetry for identical Quantum Systems Package) uses the PETSc package for sparse linear algebra methods and differential equations as basis. The aim of PsiQuaSP is to provide flexible, storage efficient and scalable code while being as user friendly as possible. It is easily applied to many quantum optical or quantum information systems with more than one multi-level system. We first review the basics of the permutation symmetry for multi-level systems in quantum master equations. The application of PsiQuaSP to quantum dynamical problems is illustrated with several typical, simple examples of open quantum optical systems.

Confidence intervals and hypothesis testing for the Permutation Entropy with an application to epilepsy

NASA Astrophysics Data System (ADS)

Traversaro, Francisco; O. Redelico, Francisco

2018-04-01

In nonlinear dynamics, and to a lesser extent in other fields, a widely used measure of complexity is the Permutation Entropy. But there is still no known method to determine the accuracy of this measure. There has been little research on the statistical properties of this quantity that characterize time series. The literature describes some resampling methods of quantities used in nonlinear dynamics - as the largest Lyapunov exponent - but these seems to fail. In this contribution, we propose a parametric bootstrap methodology using a symbolic representation of the time series to obtain the distribution of the Permutation Entropy estimator. We perform several time series simulations given by well-known stochastic processes: the 1/fα noise family, and show in each case that the proposed accuracy measure is as efficient as the one obtained by the frequentist approach of repeating the experiment. The complexity of brain electrical activity, measured by the Permutation Entropy, has been extensively used in epilepsy research for detection in dynamical changes in electroencephalogram (EEG) signal with no consideration of the variability of this complexity measure. An application of the parametric bootstrap methodology is used to compare normal and pre-ictal EEG signals.

MIDAS: Regionally linear multivariate discriminative statistical mapping.

PubMed

Varol, Erdem; Sotiras, Aristeidis; Davatzikos, Christos

2018-07-01

Statistical parametric maps formed via voxel-wise mass-univariate tests, such as the general linear model, are commonly used to test hypotheses about regionally specific effects in neuroimaging cross-sectional studies where each subject is represented by a single image. Despite being informative, these techniques remain limited as they ignore multivariate relationships in the data. Most importantly, the commonly employed local Gaussian smoothing, which is important for accounting for registration errors and making the data follow Gaussian distributions, is usually chosen in an ad hoc fashion. Thus, it is often suboptimal for the task of detecting group differences and correlations with non-imaging variables. Information mapping techniques, such as searchlight, which use pattern classifiers to exploit multivariate information and obtain more powerful statistical maps, have become increasingly popular in recent years. However, existing methods may lead to important interpretation errors in practice (i.e., misidentifying a cluster as informative, or failing to detect truly informative voxels), while often being computationally expensive. To address these issues, we introduce a novel efficient multivariate statistical framework for cross-sectional studies, termed MIDAS, seeking highly sensitive and specific voxel-wise brain maps, while leveraging the power of regional discriminant analysis. In MIDAS, locally linear discriminative learning is applied to estimate the pattern that best discriminates between two groups, or predicts a variable of interest. This pattern is equivalent to local filtering by an optimal kernel whose coefficients are the weights of the linear discriminant. By composing information from all neighborhoods that contain a given voxel, MIDAS produces a statistic that collectively reflects the contribution of the voxel to the regional classifiers as well as the discriminative power of the classifiers. Critically, MIDAS efficiently assesses the statistical significance of the derived statistic by analytically approximating its null distribution without the need for computationally expensive permutation tests. The proposed framework was extensively validated using simulated atrophy in structural magnetic resonance imaging (MRI) and further tested using data from a task-based functional MRI study as well as a structural MRI study of cognitive performance. The performance of the proposed framework was evaluated against standard voxel-wise general linear models and other information mapping methods. The experimental results showed that MIDAS achieves relatively higher sensitivity and specificity in detecting group differences. Together, our results demonstrate the potential of the proposed approach to efficiently map effects of interest in both structural and functional data. Copyright © 2018. Published by Elsevier Inc.

A chaotic cryptosystem for images based on Henon and Arnold cat map.

PubMed

Soleymani, Ali; Nordin, Md Jan; Sundararajan, Elankovan

2014-01-01

The rapid evolution of imaging and communication technologies has transformed images into a widespread data type. Different types of data, such as personal medical information, official correspondence, or governmental and military documents, are saved and transmitted in the form of images over public networks. Hence, a fast and secure cryptosystem is needed for high-resolution images. In this paper, a novel encryption scheme is presented for securing images based on Arnold cat and Henon chaotic maps. The scheme uses Arnold cat map for bit- and pixel-level permutations on plain and secret images, while Henon map creates secret images and specific parameters for the permutations. Both the encryption and decryption processes are explained, formulated, and graphically presented. The results of security analysis of five different images demonstrate the strength of the proposed cryptosystem against statistical, brute force and differential attacks. The evaluated running time for both encryption and decryption processes guarantee that the cryptosystem can work effectively in real-time applications.

A novel chaotic image encryption scheme using DNA sequence operations

NASA Astrophysics Data System (ADS)

Wang, Xing-Yuan; Zhang, Ying-Qian; Bao, Xue-Mei

2015-10-01

In this paper, we propose a novel image encryption scheme based on DNA (Deoxyribonucleic acid) sequence operations and chaotic system. Firstly, we perform bitwise exclusive OR operation on the pixels of the plain image using the pseudorandom sequences produced by the spatiotemporal chaos system, i.e., CML (coupled map lattice). Secondly, a DNA matrix is obtained by encoding the confused image using a kind of DNA encoding rule. Then we generate the new initial conditions of the CML according to this DNA matrix and the previous initial conditions, which can make the encryption result closely depend on every pixel of the plain image. Thirdly, the rows and columns of the DNA matrix are permuted. Then, the permuted DNA matrix is confused once again. At last, after decoding the confused DNA matrix using a kind of DNA decoding rule, we obtain the ciphered image. Experimental results and theoretical analysis show that the scheme is able to resist various attacks, so it has extraordinarily high security.

Evolution of a protein folding nucleus.

PubMed

Xia, Xue; Longo, Liam M; Sutherland, Mason A; Blaber, Michael

2016-07-01

The folding nucleus (FN) is a cryptic element within protein primary structure that enables an efficient folding pathway and is the postulated heritable element in the evolution of protein architecture; however, almost nothing is known regarding how the FN structurally changes as complex protein architecture evolves from simpler peptide motifs. We report characterization of the FN of a designed purely symmetric β-trefoil protein by ϕ-value analysis. We compare the structure and folding properties of key foldable intermediates along the evolutionary trajectory of the β-trefoil. The results show structural acquisition of the FN during gene fusion events, incorporating novel turn structure created by gene fusion. Furthermore, the FN is adjusted by circular permutation in response to destabilizing functional mutation. FN plasticity by way of circular permutation is made possible by the intrinsic C3 cyclic symmetry of the β-trefoil architecture, identifying a possible selective advantage that helps explain the prevalence of cyclic structural symmetry in the proteome. © 2015 The Protein Society.

Statistical physics of the symmetric group.

PubMed

Williams, Mobolaji

2017-04-01

Ordered chains (such as chains of amino acids) are ubiquitous in biological cells, and these chains perform specific functions contingent on the sequence of their components. Using the existence and general properties of such sequences as a theoretical motivation, we study the statistical physics of systems whose state space is defined by the possible permutations of an ordered list, i.e., the symmetric group, and whose energy is a function of how certain permutations deviate from some chosen correct ordering. Such a nonfactorizable state space is quite different from the state spaces typically considered in statistical physics systems and consequently has novel behavior in systems with interacting and even noninteracting Hamiltonians. Various parameter choices of a mean-field model reveal the system to contain five different physical regimes defined by two transition temperatures, a triple point, and a quadruple point. Finally, we conclude by discussing how the general analysis can be extended to state spaces with more complex combinatorial properties and to other standard questions of statistical mechanics models.

Efficiency and credit ratings: a permutation-information-theory analysis

NASA Astrophysics Data System (ADS)

Fernandez Bariviera, Aurelio; Zunino, Luciano; Belén Guercio, M.; Martinez, Lisana B.; Rosso, Osvaldo A.

2013-08-01

The role of credit rating agencies has been under severe scrutiny after the subprime crisis. In this paper we explore the relationship between credit ratings and informational efficiency of a sample of thirty nine corporate bonds of US oil and energy companies from April 2008 to November 2012. For this purpose we use a powerful statistical tool, relatively new in the financial literature: the complexity-entropy causality plane. This representation space allows us to graphically classify the different bonds according to their degree of informational efficiency. We find that this classification agrees with the credit ratings assigned by Moody’s. In particular, we detect the formation of two clusters, which correspond to the global categories of investment and speculative grades. Regarding the latter cluster, two subgroups reflect distinct levels of efficiency. Additionally, we also find an intriguing absence of correlation between informational efficiency and firm characteristics. This allows us to conclude that the proposed permutation-information-theory approach provides an alternative practical way to justify bond classification.

Statistical physics of the symmetric group

NASA Astrophysics Data System (ADS)

Williams, Mobolaji

2017-04-01

Ordered chains (such as chains of amino acids) are ubiquitous in biological cells, and these chains perform specific functions contingent on the sequence of their components. Using the existence and general properties of such sequences as a theoretical motivation, we study the statistical physics of systems whose state space is defined by the possible permutations of an ordered list, i.e., the symmetric group, and whose energy is a function of how certain permutations deviate from some chosen correct ordering. Such a nonfactorizable state space is quite different from the state spaces typically considered in statistical physics systems and consequently has novel behavior in systems with interacting and even noninteracting Hamiltonians. Various parameter choices of a mean-field model reveal the system to contain five different physical regimes defined by two transition temperatures, a triple point, and a quadruple point. Finally, we conclude by discussing how the general analysis can be extended to state spaces with more complex combinatorial properties and to other standard questions of statistical mechanics models.

Information transmission and signal permutation in active flow networks

NASA Astrophysics Data System (ADS)

Woodhouse, Francis G.; Fawcett, Joanna B.; Dunkel, Jörn

2018-03-01

Recent experiments show that both natural and artificial microswimmers in narrow channel-like geometries will self-organise to form steady, directed flows. This suggests that networks of flowing active matter could function as novel autonomous microfluidic devices. However, little is known about how information propagates through these far-from-equilibrium systems. Through a mathematical analogy with spin-ice vertex models, we investigate here the input–output characteristics of generic incompressible active flow networks (AFNs). Our analysis shows that information transport through an AFN is inherently different from conventional pressure or voltage driven networks. Active flows on hexagonal arrays preserve input information over longer distances than their passive counterparts and are highly sensitive to bulk topological defects, whose presence can be inferred from marginal input–output distributions alone. This sensitivity further allows controlled permutations on parallel inputs, revealing an unexpected link between active matter and group theory that can guide new microfluidic mixing strategies facilitated by active matter and aid the design of generic autonomous information transport networks.

A Chaotic Cryptosystem for Images Based on Henon and Arnold Cat Map

PubMed Central

Sundararajan, Elankovan

2014-01-01

The rapid evolution of imaging and communication technologies has transformed images into a widespread data type. Different types of data, such as personal medical information, official correspondence, or governmental and military documents, are saved and transmitted in the form of images over public networks. Hence, a fast and secure cryptosystem is needed for high-resolution images. In this paper, a novel encryption scheme is presented for securing images based on Arnold cat and Henon chaotic maps. The scheme uses Arnold cat map for bit- and pixel-level permutations on plain and secret images, while Henon map creates secret images and specific parameters for the permutations. Both the encryption and decryption processes are explained, formulated, and graphically presented. The results of security analysis of five different images demonstrate the strength of the proposed cryptosystem against statistical, brute force and differential attacks. The evaluated running time for both encryption and decryption processes guarantee that the cryptosystem can work effectively in real-time applications. PMID:25258724

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ferré, Grégoire; Maillet, Jean-Bernard; Stoltz, Gabriel

We present a permutation-invariant distance between atomic configurations, defined through a functional representation of atomic positions. This distance enables us to directly compare different atomic environments with an arbitrary number of particles, without going through a space of reduced dimensionality (i.e., fingerprints) as an intermediate step. Moreover, this distance is naturally invariant through permutations of atoms, avoiding the time consuming associated minimization required by other common criteria (like the root mean square distance). Finally, the invariance through global rotations is accounted for by a minimization procedure in the space of rotations solved by Monte Carlo simulated annealing. A formal frameworkmore » is also introduced, showing that the distance we propose verifies the property of a metric on the space of atomic configurations. Two examples of applications are proposed. The first one consists in evaluating faithfulness of some fingerprints (or descriptors), i.e., their capacity to represent the structural information of a configuration. The second application concerns structural analysis, where our distance proves to be efficient in discriminating different local structures and even classifying their degree of similarity.« less

Storage and computationally efficient permutations of factorized covariance and square-root information matrices

NASA Technical Reports Server (NTRS)

Muellerschoen, R. J.

1988-01-01

A unified method to permute vector-stored upper-triangular diagonal factorized covariance (UD) and vector stored upper-triangular square-root information filter (SRIF) arrays is presented. The method involves cyclical permutation of the rows and columns of the arrays and retriangularization with appropriate square-root-free fast Givens rotations or elementary slow Givens reflections. A minimal amount of computation is performed and only one scratch vector of size N is required, where N is the column dimension of the arrays. To make the method efficient for large SRIF arrays on a virtual memory machine, three additional scratch vectors each of size N are used to avoid expensive paging faults. The method discussed is compared with the methods and routines of Bierman's Estimation Subroutine Library (ESL).

1H NMR spectroscopy-based metabolomics analysis for the diagnosis of symptomatic E. coli-associated urinary tract infection (UTI).

PubMed

Lussu, Milena; Camboni, Tania; Piras, Cristina; Serra, Corrado; Del Carratore, Francesco; Griffin, Julian; Atzori, Luigi; Manzin, Aldo

2017-09-21

Urinary tract infection (UTI) is one of the most common diagnoses in girls and women, and to a lesser extent in boys and men younger than 50 years. Escherichia coli, followed by Klebsiella spp. and Proteus spp., cause 75-90% of all infections. Infection of the urinary tract is identified by growth of a significant number of a single species in the urine, in the presence of symptoms. Urinary culture is an accurate diagnostic method but takes several hours or days to be carried out. Metabolomics analysis aims to identify biomarkers that are capable of speeding up diagnosis. Urine samples from 51 patients with a prior diagnosis of Escherichia coli-associated UTI, from 21 patients with UTI caused by other pathogens (bacteria and fungi), and from 61 healthy controls were analyzed. The 1 H-NMR spectra were acquired and processed. Multivariate statistical models were applied and their performance was validated using permutation test and ROC curve. Orthogonal Partial Least Squares-discriminant Analysis (OPLS-DA) showed good separation (R 2 Y = 0.76, Q2=0.45, p < 0.001) between UTI caused by Escherichia coli and healthy controls. Acetate and trimethylamine were identified as discriminant metabolites. The concentrations of both metabolites were calculated and used to build the ROC curves. The discriminant metabolites identified were also evaluated in urine samples from patients with other pathogens infections to test their specificity. Acetate and trimethylamine were identified as optimal candidates for biomarkers for UTI diagnosis. The conclusions support the possibility of a fast diagnostic test for Escherichia coli-associated UTI using acetate and trimethylamine concentrations.

Data Mining Methods for Omics and Knowledge of Crude Medicinal Plants toward Big Data Biology

PubMed Central

Afendi, Farit M.; Ono, Naoaki; Nakamura, Yukiko; Nakamura, Kensuke; Darusman, Latifah K.; Kibinge, Nelson; Morita, Aki Hirai; Tanaka, Ken; Horai, Hisayuki; Altaf-Ul-Amin, Md.; Kanaya, Shigehiko

2013-01-01

Molecular biological data has rapidly increased with the recent progress of the Omics fields, e.g., genomics, transcriptomics, proteomics and metabolomics that necessitates the development of databases and methods for efficient storage, retrieval, integration and analysis of massive data. The present study reviews the usage of KNApSAcK Family DB in metabolomics and related area, discusses several statistical methods for handling multivariate data and shows their application on Indonesian blended herbal medicines (Jamu) as a case study. Exploration using Biplot reveals many plants are rarely utilized while some plants are highly utilized toward specific efficacy. Furthermore, the ingredients of Jamu formulas are modeled using Partial Least Squares Discriminant Analysis (PLS-DA) in order to predict their efficacy. The plants used in each Jamu medicine served as the predictors, whereas the efficacy of each Jamu provided the responses. This model produces 71.6% correct classification in predicting efficacy. Permutation test then is used to determine plants that serve as main ingredients in Jamu formula by evaluating the significance of the PLS-DA coefficients. Next, in order to explain the role of plants that serve as main ingredients in Jamu medicines, information of pharmacological activity of the plants is added to the predictor block. Then N-PLS-DA model, multiway version of PLS-DA, is utilized to handle the three-dimensional array of the predictor block. The resulting N-PLS-DA model reveals that the effects of some pharmacological activities are specific for certain efficacy and the other activities are diverse toward many efficacies. Mathematical modeling introduced in the present study can be utilized in global analysis of big data targeting to reveal the underlying biology. PMID:24688691

Permutation entropy analysis of heart rate variability for the assessment of cardiovascular autonomic neuropathy in type 1 diabetes mellitus.

PubMed

Carricarte Naranjo, Claudia; Sanchez-Rodriguez, Lazaro M; Brown Martínez, Marta; Estévez Báez, Mario; Machado García, Andrés

2017-07-01

Heart rate variability (HRV) analysis is a relevant tool for the diagnosis of cardiovascular autonomic neuropathy (CAN). To our knowledge, no previous investigation on CAN has assessed the complexity of HRV from an ordinal perspective. Therefore, the aim of this work is to explore the potential of permutation entropy (PE) analysis of HRV complexity for the assessment of CAN. For this purpose, we performed a short-term PE analysis of HRV in healthy subjects and type 1 diabetes mellitus patients, including patients with CAN. Standard HRV indicators were also calculated in the control group. A discriminant analysis was used to select the variables combination with best discriminative power between control and CAN patients groups, as well as for classifying cases. We found that for some specific temporal scales, PE indicators were significantly lower in CAN patients than those calculated for controls. In such cases, there were ordinal patterns with high probabilities of occurrence, while others were hardly found. We posit this behavior occurs due to a decrease of HRV complexity in the diseased system. Discriminant functions based on PE measures or probabilities of occurrence of ordinal patterns provided an average of 75% and 96% classification accuracy. Correlations of PE and HRV measures showed to depend only on temporal scale, regardless of pattern length. PE analysis at some specific temporal scales, seem to provide additional information to that obtained with traditional HRV methods. We concluded that PE analysis of HRV is a promising method for the assessment of CAN. Copyright © 2017 Elsevier Ltd. All rights reserved.

Dominant Tree Species and Soil Type Affect the Fungal Community Structure in a Boreal Peatland Forest.

PubMed

Sun, Hui; Terhonen, Eeva; Kovalchuk, Andriy; Tuovila, Hanna; Chen, Hongxin; Oghenekaro, Abbot O; Heinonsalo, Jussi; Kohler, Annegret; Kasanen, Risto; Vasander, Harri; Asiegbu, Fred O

2016-05-01

Boreal peatlands play a crucial role in global carbon cycling, acting as an important carbon reservoir. However, little information is available on how peatland microbial communities are influenced by natural variability or human-induced disturbances. In this study, we have investigated the fungal diversity and community structure of both the organic soil layer and buried wood in boreal forest soils using high-throughput sequencing of the internal transcribed spacer (ITS) region. We have also compared the fungal communities during the primary colonization of wood with those of the surrounding soils. A permutational multivariate analysis of variance (PERMANOVA) confirmed that the community composition significantly differed between soil types (P< 0.001) and tree species (P< 0.001). The distance-based linear models analysis showed that environmental variables were significantly correlated with community structure (P< 0.04). The availability of soil nutrients (Ca [P= 0.002], Fe [P= 0.003], and P [P= 0.003]) within the site was an important factor in the fungal community composition. The species richness in wood was significantly lower than in the corresponding soil (P< 0.004). The results of the molecular identification were supplemented by fruiting body surveys. Seven of the genera of Agaricomycotina identified in our surveys were among the top 20 genera observed in pyrosequencing data. Our study is the first, to our knowledge, fungal high-throughput next-generation sequencing study performed on peatlands; it further provides a baseline for the investigation of the dynamics of the fungal community in the boreal peatlands. Copyright © 2016, American Society for Microbiology. All Rights Reserved.

Predicting invertebrate assemblage composition from harvesting pressure and environmental characteristics on tropical reef flats

NASA Astrophysics Data System (ADS)

Jimenez, H.; Dumas, P.; Ponton, D.; Ferraris, J.

2012-03-01

Invertebrates represent an essential component of coral reef ecosystems; they are ecologically important and a major resource, but their assemblages remain largely unknown, particularly on Pacific islands. Understanding their distribution and building predictive models of community composition as a function of environmental variables therefore constitutes a key issue for resource management. The goal of this study was to define and classify the main environmental factors influencing tropical invertebrate distributions in New Caledonian reef flats and to test the resulting predictive model. Invertebrate assemblages were sampled by visual counting during 2 years and 2 seasons, then coupled to different environmental conditions (habitat composition, hydrodynamics and sediment characteristics) and harvesting status (MPA vs. non-MPA and islets vs. coastal flats). Environmental conditions were described by a principal component analysis (PCA), and contributing variables were selected. Permutational analysis of variance (PERMANOVA) was used to test the effects of different factors (status, flat, year and season) on the invertebrate assemblage composition. Multivariate regression trees (MRT) were then used to hierarchically classify the effects of environmental and harvesting variables. MRT model explained at least 60% of the variation in structure of invertebrate communities. Results highlighted the influence of status (MPA vs. non-MPA) and location (islet vs. coastal flat), followed by habitat composition, organic matter content, hydrodynamics and sampling year. Predicted assemblages defined by indicator families were very different for each environment-exploitation scenario and correctly matched a calibration data matrix. Predictions from MRT including both environmental variables and harvesting pressure can be useful for management of invertebrates in coral reef environments.

Long-term experimental warming alters nitrogen-cycling communities but site factors remain the primary drivers of community structure in high arctic tundra soils.

PubMed

Walker, Jennifer K M; Egger, Keith N; Henry, Gregory H R

2008-09-01

Arctic air temperatures are expected to rise significantly over the next century. Experimental warming of arctic tundra has been shown to increase plant productivity and cause community shifts and may also alter microbial community structure. Hence, the objective of this study was to determine whether experimental warming caused shifts in soil microbial communities by measuring changes in the frequency, relative abundance and/or richness of nosZ and nifH genotypes. Five sites at a high arctic coastal lowland were subjected to a 13-year warming experiment using open-top chambers (OTCs). Sites differed by dominant plant community, soil parent material and/or moisture regimen. Six soil cores were collected from each of four replicate OTC and ambient plots at each site and subdivided into upper and lower samples. Differences in frequency and relative abundance of terminal restriction fragments were assessed graphically by two-way cluster analysis and tested statistically with permutational multivariate analysis of variance (ANOVA). Genotypic richness was compared using factorial ANOVA. The genotype frequency, relative abundance and genotype richness of both nosZ and nifH communities differed significantly by site, and by OTC treatment and/or depth at some sites. The site that showed the most pronounced treatment effect was a wet sedge meadow, where community structure and genotype richness of both nosZ and nifH were significantly affected by warming. Although warming was an important factor affecting these communities at some sites at this high arctic lowland, overall, site factors were the main determinants of community structure.

Gut microbiota in early pediatric multiple sclerosis: a case-control study.

PubMed

Tremlett, Helen; Fadrosh, Douglas W; Faruqi, Ali A; Zhu, Feng; Hart, Janace; Roalstad, Shelly; Graves, Jennifer; Lynch, Susan; Waubant, Emmanuelle

2016-08-01

Alterations in the gut microbial community composition may be influential in neurological disease. Microbial community profiles were compared between early onset pediatric multiple sclerosis (MS) and control children similar for age and sex. Children ≤18 years old within 2 years of MS onset or controls without autoimmune disorders attending a University of California, San Francisco, USA, pediatric clinic were examined for fecal bacterial community composition and predicted function by 16S ribosomal RNA sequencing and phylogenetic reconstruction of unobserved states (PICRUSt) analysis. Associations between subject characteristics and the microbiota, including beta diversity and taxa abundance, were identified using non-parametric tests, permutational multivariate analysis of variance and negative binomial regression. Eighteen relapsing-remitting MS cases and 17 controls (mean age 13 years; range 4-18) were studied. Cases had a short disease duration (mean 11 months; range 2-24) and half were immunomodulatory drug (IMD) naïve. Whilst overall gut bacterial beta diversity was not significantly related to MS status, IMD exposure was (Canberra, P < 0.02). However, relative to controls, MS cases had a significant enrichment in relative abundance for members of the Desulfovibrionaceae (Bilophila, Desulfovibrio and Christensenellaceae) and depletion in Lachnospiraceae and Ruminococcaceae (all P and q < 0.000005). Microbial genes predicted as enriched in MS versus controls included those involved in glutathione metabolism (Mann-Whitney, P = 0.017), findings that were consistent regardless of IMD exposure. In recent onset pediatric MS, perturbations in the gut microbiome composition were observed, in parallel with predicted enrichment of metabolic pathways associated with neurodegeneration. Findings were suggestive of a pro-inflammatory milieu. © 2016 EAN.

Dominant Tree Species and Soil Type Affect the Fungal Community Structure in a Boreal Peatland Forest

PubMed Central

Terhonen, Eeva; Kovalchuk, Andriy; Tuovila, Hanna; Chen, Hongxin; Oghenekaro, Abbot O.; Heinonsalo, Jussi; Kohler, Annegret; Kasanen, Risto; Vasander, Harri; Asiegbu, Fred O.

2016-01-01

Boreal peatlands play a crucial role in global carbon cycling, acting as an important carbon reservoir. However, little information is available on how peatland microbial communities are influenced by natural variability or human-induced disturbances. In this study, we have investigated the fungal diversity and community structure of both the organic soil layer and buried wood in boreal forest soils using high-throughput sequencing of the internal transcribed spacer (ITS) region. We have also compared the fungal communities during the primary colonization of wood with those of the surrounding soils. A permutational multivariate analysis of variance (PERMANOVA) confirmed that the community composition significantly differed between soil types (P < 0.001) and tree species (P < 0.001). The distance-based linear models analysis showed that environmental variables were significantly correlated with community structure (P < 0.04). The availability of soil nutrients (Ca [P = 0.002], Fe [P = 0.003], and P [P = 0.003]) within the site was an important factor in the fungal community composition. The species richness in wood was significantly lower than in the corresponding soil (P < 0.004). The results of the molecular identification were supplemented by fruiting body surveys. Seven of the genera of Agaricomycotina identified in our surveys were among the top 20 genera observed in pyrosequencing data. Our study is the first, to our knowledge, fungal high-throughput next-generation sequencing study performed on peatlands; it further provides a baseline for the investigation of the dynamics of the fungal community in the boreal peatlands. PMID:26896139

Using empirical Bayes predictors from generalized linear mixed models to test and visualize associations among longitudinal outcomes.

PubMed

Mikulich-Gilbertson, Susan K; Wagner, Brandie D; Grunwald, Gary K; Riggs, Paula D; Zerbe, Gary O

2018-01-01

Medical research is often designed to investigate changes in a collection of response variables that are measured repeatedly on the same subjects. The multivariate generalized linear mixed model (MGLMM) can be used to evaluate random coefficient associations (e.g. simple correlations, partial regression coefficients) among outcomes that may be non-normal and differently distributed by specifying a multivariate normal distribution for their random effects and then evaluating the latent relationship between them. Empirical Bayes predictors are readily available for each subject from any mixed model and are observable and hence, plotable. Here, we evaluate whether second-stage association analyses of empirical Bayes predictors from a MGLMM, provide a good approximation and visual representation of these latent association analyses using medical examples and simulations. Additionally, we compare these results with association analyses of empirical Bayes predictors generated from separate mixed models for each outcome, a procedure that could circumvent computational problems that arise when the dimension of the joint covariance matrix of random effects is large and prohibits estimation of latent associations. As has been shown in other analytic contexts, the p-values for all second-stage coefficients that were determined by naively assuming normality of empirical Bayes predictors provide a good approximation to p-values determined via permutation analysis. Analyzing outcomes that are interrelated with separate models in the first stage and then associating the resulting empirical Bayes predictors in a second stage results in different mean and covariance parameter estimates from the maximum likelihood estimates generated by a MGLMM. The potential for erroneous inference from using results from these separate models increases as the magnitude of the association among the outcomes increases. Thus if computable, scatterplots of the conditionally independent empirical Bayes predictors from a MGLMM are always preferable to scatterplots of empirical Bayes predictors generated by separate models, unless the true association between outcomes is zero.

NASA thesaurus. Volume 2: Access vocabulary

NASA Technical Reports Server (NTRS)

1988-01-01

The access vocabulary, which is essentially a permuted index, provides access to any word or number in authorized postable and nonpostable terms. Additional entries include postable and nonpostable terms, other word entries and pseudo-multiword terms that are permutations of words that contain words within words. The access vocabulary contains almost 42,000 entries that give increased access to the hierarchies in Volume 1 - Hierarchical Listing.

Circular permutation of the starch-binding domain: inversion of ligand selectivity with increased affinity.

PubMed

Stephen, Preyesh; Tseng, Kai-Li; Liu, Yu-Nan; Lyu, Ping-Chiang

2012-03-07

Proteins containing starch-binding domains (SBDs) are used in a variety of scientific and technological applications. A circularly permutated SBD (CP90) with improved affinity and selectivity toward longer-chain carbohydrates was synthesized, suggesting that a new starch-binding protein may be developed for specific scientific and industrial applications. This journal is © The Royal Society of Chemistry 2012

Sampling solution traces for the problem of sorting permutations by signed reversals

PubMed Central

2012-01-01

Background Traditional algorithms to solve the problem of sorting by signed reversals output just one optimal solution while the space of all optimal solutions can be huge. A so-called trace represents a group of solutions which share the same set of reversals that must be applied to sort the original permutation following a partial ordering. By using traces, we therefore can represent the set of optimal solutions in a more compact way. Algorithms for enumerating the complete set of traces of solutions were developed. However, due to their exponential complexity, their practical use is limited to small permutations. A partial enumeration of traces is a sampling of the complete set of traces and can be an alternative for the study of distinct evolutionary scenarios of big permutations. Ideally, the sampling should be done uniformly from the space of all optimal solutions. This is however conjectured to be ♯P-complete. Results We propose and evaluate three algorithms for producing a sampling of the complete set of traces that instead can be shown in practice to preserve some of the characteristics of the space of all solutions. The first algorithm (RA) performs the construction of traces through a random selection of reversals on the list of optimal 1-sequences. The second algorithm (DFALT) consists in a slight modification of an algorithm that performs the complete enumeration of traces. Finally, the third algorithm (SWA) is based on a sliding window strategy to improve the enumeration of traces. All proposed algorithms were able to enumerate traces for permutations with up to 200 elements. Conclusions We analysed the distribution of the enumerated traces with respect to their height and average reversal length. Various works indicate that the reversal length can be an important aspect in genome rearrangements. The algorithms RA and SWA show a tendency to lose traces with high average reversal length. Such traces are however rare, and qualitatively our results show that, for testable-sized permutations, the algorithms DFALT and SWA produce distributions which approximate the reversal length distributions observed with a complete enumeration of the set of traces. PMID:22704580

Why Did They Fight the Great War? A Multi-Level Class Analysis of the Causes of the First World War

ERIC Educational Resources Information Center

Gillette, Aaron

2006-01-01

The question, "What were the causes of World War I?," has become one of the classic historical debates of which there seem to be endless permutations. In the past 90 years historians, journalists, and politicians have offered many more or less rational explanations for the war. Although at least some of the usual "causes"…

Multiscale permutation entropy analysis of EEG recordings during sevoflurane anesthesia

NASA Astrophysics Data System (ADS)

Li, Duan; Li, Xiaoli; Liang, Zhenhu; Voss, Logan J.; Sleigh, Jamie W.

2010-08-01

Electroencephalogram (EEG) monitoring of the effect of anesthetic drugs on the central nervous system has long been used in anesthesia research. Several methods based on nonlinear dynamics, such as permutation entropy (PE), have been proposed to analyze EEG series during anesthesia. However, these measures are still single-scale based and may not completely describe the dynamical characteristics of complex EEG series. In this paper, a novel measure combining multiscale PE information, called CMSPE (composite multi-scale permutation entropy), was proposed for quantifying the anesthetic drug effect on EEG recordings during sevoflurane anesthesia. Three sets of simulated EEG series during awake, light and deep anesthesia were used to select the parameters for the multiscale PE analysis: embedding dimension m, lag τ and scales to be integrated into the CMSPE index. Then, the CMSPE index and raw single-scale PE index were applied to EEG recordings from 18 patients who received sevoflurane anesthesia. Pharmacokinetic/pharmacodynamic (PKPD) modeling was used to relate the measured EEG indices and the anesthetic drug concentration. Prediction probability (Pk) statistics and correlation analysis with the response entropy (RE) index, derived from the spectral entropy (M-entropy module; GE Healthcare, Helsinki, Finland), were investigated to evaluate the effectiveness of the new proposed measure. It was found that raw single-scale PE was blind to subtle transitions between light and deep anesthesia, while the CMSPE index tracked these changes accurately. Around the time of loss of consciousness, CMSPE responded significantly more rapidly than the raw PE, with the absolute slopes of linearly fitted response versus time plots of 0.12 (0.09-0.15) and 0.10 (0.06-0.13), respectively. The prediction probability Pk of 0.86 (0.85-0.88) and 0.85 (0.80-0.86) for CMSPE and raw PE indicated that the CMSPE index correlated well with the underlying anesthetic effect. The correlation coefficient for the comparison between the CMSPE index and RE index of 0.84 (0.80-0.88) was significantly higher than the raw PE index of 0.75 (0.66-0.84). The results show that the CMSPE outperforms the raw single-scale PE in reflecting the sevoflurane drug effect on the central nervous system.

Efficient computation of significance levels for multiple associations in large studies of correlated data, including genomewide association studies.

PubMed

Dudbridge, Frank; Koeleman, Bobby P C

2004-09-01

Large exploratory studies, including candidate-gene-association testing, genomewide linkage-disequilibrium scans, and array-expression experiments, are becoming increasingly common. A serious problem for such studies is that statistical power is compromised by the need to control the false-positive rate for a large family of tests. Because multiple true associations are anticipated, methods have been proposed that combine evidence from the most significant tests, as a more powerful alternative to individually adjusted tests. The practical application of these methods is currently limited by a reliance on permutation testing to account for the correlated nature of single-nucleotide polymorphism (SNP)-association data. On a genomewide scale, this is both very time-consuming and impractical for repeated explorations with standard marker panels. Here, we alleviate these problems by fitting analytic distributions to the empirical distribution of combined evidence. We fit extreme-value distributions for fixed lengths of combined evidence and a beta distribution for the most significant length. An initial phase of permutation sampling is required to fit these distributions, but it can be completed more quickly than a simple permutation test and need be done only once for each panel of tests, after which the fitted parameters give a reusable calibration of the panel. Our approach is also a more efficient alternative to a standard permutation test. We demonstrate the accuracy of our approach and compare its efficiency with that of permutation tests on genomewide SNP data released by the International HapMap Consortium. The estimation of analytic distributions for combined evidence will allow these powerful methods to be applied more widely in large exploratory studies.

Inference With Difference-in-Differences With a Small Number of Groups: A Review, Simulation Study, and Empirical Application Using SHARE Data.

PubMed

Rokicki, Slawa; Cohen, Jessica; Fink, Günther; Salomon, Joshua A; Landrum, Mary Beth

2018-01-01

Difference-in-differences (DID) estimation has become increasingly popular as an approach to evaluate the effect of a group-level policy on individual-level outcomes. Several statistical methodologies have been proposed to correct for the within-group correlation of model errors resulting from the clustering of data. Little is known about how well these corrections perform with the often small number of groups observed in health research using longitudinal data. First, we review the most commonly used modeling solutions in DID estimation for panel data, including generalized estimating equations (GEE), permutation tests, clustered standard errors (CSE), wild cluster bootstrapping, and aggregation. Second, we compare the empirical coverage rates and power of these methods using a Monte Carlo simulation study in scenarios in which we vary the degree of error correlation, the group size balance, and the proportion of treated groups. Third, we provide an empirical example using the Survey of Health, Ageing, and Retirement in Europe. When the number of groups is small, CSE are systematically biased downwards in scenarios when data are unbalanced or when there is a low proportion of treated groups. This can result in over-rejection of the null even when data are composed of up to 50 groups. Aggregation, permutation tests, bias-adjusted GEE, and wild cluster bootstrap produce coverage rates close to the nominal rate for almost all scenarios, though GEE may suffer from low power. In DID estimation with a small number of groups, analysis using aggregation, permutation tests, wild cluster bootstrap, or bias-adjusted GEE is recommended.

How to think about indiscernible particles

NASA Astrophysics Data System (ADS)

Giglio, Daniel Joseph

Permutation symmetries which arise in quantum mechanics pose an intriguing problem. It is not clear that particles which exhibit permutation symmetries (i.e. particles which are indiscernible, meaning that they can be swapped with each other without this yielding a new physical state) qualify as "objects" in any reasonable sense of the term. One solution to this puzzle, which I attribute to W.V. Quine, would have us eliminate such particles from our ontology altogether in order to circumvent the metaphysical vexations caused by permutation symmetries. In this essay I argue that Quine's solution is too rash, and in its place I suggest a novel solution based on altering some of the language of quantum mechanics. Before launching into the technical details of indiscernible particles, however, I begin this essay with some remarks on the methodology -- instrumentalism -- which motivates my arguments.

Fermion systems in discrete space-time

NASA Astrophysics Data System (ADS)

Finster, Felix

2007-05-01

Fermion systems in discrete space-time are introduced as a model for physics on the Planck scale. We set up a variational principle which describes a non-local interaction of all fermions. This variational principle is symmetric under permutations of the discrete space-time points. We explain how for minimizers of the variational principle, the fermions spontaneously break this permutation symmetry and induce on space-time a discrete causal structure.

Dynamic Testing and Automatic Repair of Reconfigurable Wiring Harnesses

DTIC Science & Technology

2006-11-27

Switch An M ×N grid of switches configured to provide a M -input, N -output routing network. Permutation Network A permutation network performs an...wiring reduces the effective advantage of their reduced switch count, particularly when considering that regular grids (crossbar switches being a...are connected to. The outline circuit shown in Fig. 20 shows how a suitable ‘discovery probe’ might be implemented. The circuit shows a UART

Research of Planetary Gear Fault Diagnosis Based on Permutation Entropy of CEEMDAN and ANFIS

PubMed Central

Kuai, Moshen; Cheng, Gang; Li, Yong

2018-01-01

For planetary gear has the characteristics of small volume, light weight and large transmission ratio, it is widely used in high speed and high power mechanical system. Poor working conditions result in frequent failures of planetary gear. A method is proposed for diagnosing faults in planetary gear based on permutation entropy of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) Adaptive Neuro-fuzzy Inference System (ANFIS) in this paper. The original signal is decomposed into 6 intrinsic mode functions (IMF) and residual components by CEEMDAN. Since the IMF contains the main characteristic information of planetary gear faults, time complexity of IMFs are reflected by permutation entropies to quantify the fault features. The permutation entropies of each IMF component are defined as the input of ANFIS, and its parameters and membership functions are adaptively adjusted according to training samples. Finally, the fuzzy inference rules are determined, and the optimal ANFIS is obtained. The overall recognition rate of the test sample used for ANFIS is 90%, and the recognition rate of gear with one missing tooth is relatively high. The recognition rates of different fault gears based on the method can also achieve better results. Therefore, the proposed method can be applied to planetary gear fault diagnosis effectively. PMID:29510569

Tolerance of a Knotted Near-Infrared Fluorescent Protein to Random Circular Permutation.

PubMed

Pandey, Naresh; Kuypers, Brianna E; Nassif, Barbara; Thomas, Emily E; Alnahhas, Razan N; Segatori, Laura; Silberg, Jonathan J

2016-07-12

Bacteriophytochrome photoreceptors (BphP) are knotted proteins that have been developed as near-infrared fluorescent protein (iRFP) reporters of gene expression. To explore how rearrangements in the peptides that interlace into the knot within the BphP photosensory core affect folding, we subjected iRFPs to random circular permutation using an improved transposase mutagenesis strategy and screened for variants that fluoresce. We identified 27 circularly permuted iRFPs that display biliverdin-dependent fluorescence in Escherichia coli. The variants with the brightest whole cell fluorescence initiated translation at residues near the domain linker and knot tails, although fluorescent variants that initiated translation within the PAS and GAF domains were discovered. Circularly permuted iRFPs retained sufficient cofactor affinity to fluoresce in tissue culture without the addition of biliverdin, and one variant displayed enhanced fluorescence when expressed in bacteria and tissue culture. This variant displayed a quantum yield similar to that of iRFPs but exhibited increased resistance to chemical denaturation, suggesting that the observed increase in the magnitude of the signal arose from more efficient protein maturation. These results show how the contact order of a knotted BphP can be altered without disrupting chromophore binding and fluorescence, an important step toward the creation of near-infrared biosensors with expanded chemical sensing functions for in vivo imaging.

Tolerance of a knotted near infrared fluorescent protein to random circular permutation

PubMed Central

Pandey, Naresh; Kuypers, Brianna E.; Nassif, Barbara; Thomas, Emily E.; Alnahhas, Razan N.; Segatori, Laura; Silberg, Jonathan J.

2016-01-01

Bacteriophytochrome photoreceptors (BphP) are knotted proteins that have been developed as near-infrared fluorescent protein (iRFP) reporters of gene expression. To explore how rearrangements in the peptides that interlace into the knot within the BphP photosensory core affect folding, we subjected iRFP to random circular permutation using an improved transposase mutagenesis strategy and screened for variants that fluoresce. We identified twenty seven circularly permuted iRFP that display biliverdin-dependent fluorescence in Escherichia coli. The variants with the brightest whole cell fluorescence initiated translation at residues near the domain linker and knot tails, although fluorescent variants were discovered that initiated translation within the PAS and GAF domains. Circularly permuted iRFP retained sufficient cofactor affinity to fluoresce in tissue culture without the addition of biliverdin, and one variant displayed enhanced fluorescence when expressed in bacteria and tissue culture. This variant displayed a similar quantum yield as iRFP, but exhibited increased resistance to chemical denaturation, suggesting that the observed signal increase arose from more efficient protein maturation. These results show how the contact order of a knotted BphP can be altered without disrupting chromophore binding and fluorescence, an important step towards the creation of near-infrared biosensors with expanded chemical-sensing functions for in vivo imaging. PMID:27304983

Research of Planetary Gear Fault Diagnosis Based on Permutation Entropy of CEEMDAN and ANFIS.

PubMed

Kuai, Moshen; Cheng, Gang; Pang, Yusong; Li, Yong

2018-03-05

For planetary gear has the characteristics of small volume, light weight and large transmission ratio, it is widely used in high speed and high power mechanical system. Poor working conditions result in frequent failures of planetary gear. A method is proposed for diagnosing faults in planetary gear based on permutation entropy of Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN) Adaptive Neuro-fuzzy Inference System (ANFIS) in this paper. The original signal is decomposed into 6 intrinsic mode functions (IMF) and residual components by CEEMDAN. Since the IMF contains the main characteristic information of planetary gear faults, time complexity of IMFs are reflected by permutation entropies to quantify the fault features. The permutation entropies of each IMF component are defined as the input of ANFIS, and its parameters and membership functions are adaptively adjusted according to training samples. Finally, the fuzzy inference rules are determined, and the optimal ANFIS is obtained. The overall recognition rate of the test sample used for ANFIS is 90%, and the recognition rate of gear with one missing tooth is relatively high. The recognition rates of different fault gears based on the method can also achieve better results. Therefore, the proposed method can be applied to planetary gear fault diagnosis effectively.

A Novel Bit-level Image Encryption Method Based on Chaotic Map and Dynamic Grouping

NASA Astrophysics Data System (ADS)

Zhang, Guo-Ji; Shen, Yan

2012-10-01

In this paper, a novel bit-level image encryption method based on dynamic grouping is proposed. In the proposed method, the plain-image is divided into several groups randomly, then permutation-diffusion process on bit level is carried out. The keystream generated by logistic map is related to the plain-image, which confuses the relationship between the plain-image and the cipher-image. The computer simulation results of statistical analysis, information entropy analysis and sensitivity analysis show that the proposed encryption method is secure and reliable enough to be used for communication application.

Comparison of a non-stationary voxelation-corrected cluster-size test with TFCE for group-Level MRI inference.

PubMed

Li, Huanjie; Nickerson, Lisa D; Nichols, Thomas E; Gao, Jia-Hong

2017-03-01

Two powerful methods for statistical inference on MRI brain images have been proposed recently, a non-stationary voxelation-corrected cluster-size test (CST) based on random field theory and threshold-free cluster enhancement (TFCE) based on calculating the level of local support for a cluster, then using permutation testing for inference. Unlike other statistical approaches, these two methods do not rest on the assumptions of a uniform and high degree of spatial smoothness of the statistic image. Thus, they are strongly recommended for group-level fMRI analysis compared to other statistical methods. In this work, the non-stationary voxelation-corrected CST and TFCE methods for group-level analysis were evaluated for both stationary and non-stationary images under varying smoothness levels, degrees of freedom and signal to noise ratios. Our results suggest that, both methods provide adequate control for the number of voxel-wise statistical tests being performed during inference on fMRI data and they are both superior to current CSTs implemented in popular MRI data analysis software packages. However, TFCE is more sensitive and stable for group-level analysis of VBM data. Thus, the voxelation-corrected CST approach may confer some advantages by being computationally less demanding for fMRI data analysis than TFCE with permutation testing and by also being applicable for single-subject fMRI analyses, while the TFCE approach is advantageous for VBM data. Hum Brain Mapp 38:1269-1280, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

General Rotorcraft Aeromechanical Stability Program (GRASP) - Theory Manual

DTIC Science & Technology

1990-10-01

the A basis. Two symbols frequently encountered in vector operations that use index notation are the Kronecker delta eij and the Levi - Civita epsilon...Blade root cutout fijk Levi - Civita epsilon permutation symbol 0 pretwist angle 0’ pretwist per unit length (d;) Oi Tait-Bryan angles K~i moment strains...the components of the identity tensor in a Cartesian coordinate system, while the Levi Civita epsilon consists of components of the permutation

Using permutations to detect dependence between time series

NASA Astrophysics Data System (ADS)

Cánovas, Jose S.; Guillamón, Antonio; Ruíz, María del Carmen

2011-07-01

In this paper, we propose an independence test between two time series which is based on permutations. The proposed test can be carried out by means of different common statistics such as Pearson’s chi-square or the likelihood ratio. We also point out why an exact test is necessary. Simulated and real data (return exchange rates between several currencies) reveal the capacity of this test to detect linear and nonlinear dependences.

Testing of Error-Correcting Sparse Permutation Channel Codes

NASA Technical Reports Server (NTRS)

Shcheglov, Kirill, V.; Orlov, Sergei S.

2008-01-01

A computer program performs Monte Carlo direct numerical simulations for testing sparse permutation channel codes, which offer strong error-correction capabilities at high code rates and are considered especially suitable for storage of digital data in holographic and volume memories. A word in a code of this type is characterized by, among other things, a sparseness parameter (M) and a fixed number (K) of 1 or "on" bits in a channel block length of N.

Scrambled Sobol Sequences via Permutation

DTIC Science & Technology

2009-01-01

LCG LCG64 LFG MLFG PMLCG Sobol Scrambler PermutationScrambler LinearScrambler <<uses>> PermuationFactory StaticFactory DynamicFactory <<uses>> Figure 3...Phy., 19:252–256, 1979. [2] Emanouil I. Atanassov. A new efficient algorithm for generating the scrambled sobol ’ sequence. In NMA ’02: Revised Papers...Deidre W.Evan, and Micheal Mascagni. On the scrambled sobol sequence. In ICCS2005, pages 775–782, 2005. [7] Richard Durstenfeld. Algorithm 235: Random

Evaluation of Second-Level Inference in fMRI Analysis

PubMed Central

Roels, Sanne P.; Loeys, Tom; Moerkerke, Beatrijs

2016-01-01

We investigate the impact of decisions in the second-level (i.e., over subjects) inferential process in functional magnetic resonance imaging on (1) the balance between false positives and false negatives and on (2) the data-analytical stability, both proxies for the reproducibility of results. Second-level analysis based on a mass univariate approach typically consists of 3 phases. First, one proceeds via a general linear model for a test image that consists of pooled information from different subjects. We evaluate models that take into account first-level (within-subjects) variability and models that do not take into account this variability. Second, one proceeds via inference based on parametrical assumptions or via permutation-based inference. Third, we evaluate 3 commonly used procedures to address the multiple testing problem: familywise error rate correction, False Discovery Rate (FDR) correction, and a two-step procedure with minimal cluster size. Based on a simulation study and real data we find that the two-step procedure with minimal cluster size results in most stable results, followed by the familywise error rate correction. The FDR results in most variable results, for both permutation-based inference and parametrical inference. Modeling the subject-specific variability yields a better balance between false positives and false negatives when using parametric inference. PMID:26819578

Data Decomposition Techniques with Multi-Scale Permutation Entropy Calculations for Bearing Fault Diagnosis

PubMed Central

Yasir, Muhammad Naveed; Koh, Bong-Hwan

2018-01-01

This paper presents the local mean decomposition (LMD) integrated with multi-scale permutation entropy (MPE), also known as LMD-MPE, to investigate the rolling element bearing (REB) fault diagnosis from measured vibration signals. First, the LMD decomposed the vibration data or acceleration measurement into separate product functions that are composed of both amplitude and frequency modulation. MPE then calculated the statistical permutation entropy from the product functions to extract the nonlinear features to assess and classify the condition of the healthy and damaged REB system. The comparative experimental results of the conventional LMD-based multi-scale entropy and MPE were presented to verify the authenticity of the proposed technique. The study found that LMD-MPE’s integrated approach provides reliable, damage-sensitive features when analyzing the bearing condition. The results of REB experimental datasets show that the proposed approach yields more vigorous outcomes than existing methods. PMID:29690526

Optimization and experimental realization of the quantum permutation algorithm

NASA Astrophysics Data System (ADS)

Yalçınkaya, I.; Gedik, Z.

2017-12-01

The quantum permutation algorithm provides computational speed-up over classical algorithms for determining the parity of a given cyclic permutation. For its n -qubit implementations, the number of required quantum gates scales quadratically with n due to the quantum Fourier transforms included. We show here for the n -qubit case that the algorithm can be simplified so that it requires only O (n ) quantum gates, which theoretically reduces the complexity of the implementation. To test our results experimentally, we utilize IBM's 5-qubit quantum processor to realize the algorithm by using the original and simplified recipes for the 2-qubit case. It turns out that the latter results in a significantly higher success probability which allows us to verify the algorithm more precisely than the previous experimental realizations. We also verify the algorithm for the first time for the 3-qubit case with a considerable success probability by taking the advantage of our simplified scheme.

A faster 1.375-approximation algorithm for sorting by transpositions.

PubMed

Cunha, Luís Felipe I; Kowada, Luis Antonio B; Hausen, Rodrigo de A; de Figueiredo, Celina M H

2015-11-01

Sorting by Transpositions is an NP-hard problem for which several polynomial-time approximation algorithms have been developed. Hartman and Shamir (2006) developed a 1.5-approximation [Formula: see text] algorithm, whose running time was improved to O(nlogn) by Feng and Zhu (2007) with a data structure they defined, the permutation tree. Elias and Hartman (2006) developed a 1.375-approximation O(n(2)) algorithm, and Firoz et al. (2011) claimed an improvement to the running time, from O(n(2)) to O(nlogn), by using the permutation tree. We provide counter-examples to the correctness of Firoz et al.'s strategy, showing that it is not possible to reach a component by sufficient extensions using the method proposed by them. In addition, we propose a 1.375-approximation algorithm, modifying Elias and Hartman's approach with the use of permutation trees and achieving O(nlogn) time.

Phase Transitions in Definite Total Spin States of Two-Component Fermi Gases.

PubMed

Yurovsky, Vladimir A

2017-05-19

Second-order phase transitions have no latent heat and are characterized by a change in symmetry. In addition to the conventional symmetric and antisymmetric states under permutations of bosons and fermions, mathematical group-representation theory allows for non-Abelian permutation symmetry. Such symmetry can be hidden in states with defined total spins of spinor gases, which can be formed in optical cavities. The present work shows that the symmetry reveals itself in spin-independent or coordinate-independent properties of these gases, namely as non-Abelian entropy in thermodynamic properties. In weakly interacting Fermi gases, two phases appear associated with fermionic and non-Abelian symmetry under permutations of particle states, respectively. The second-order transitions between the phases are characterized by discontinuities in specific heat. Unlike other phase transitions, the present ones are not caused by interactions and can appear even in ideal gases. Similar effects in Bose gases and strong interactions are discussed.

Data Decomposition Techniques with Multi-Scale Permutation Entropy Calculations for Bearing Fault Diagnosis.

PubMed

Yasir, Muhammad Naveed; Koh, Bong-Hwan

2018-04-21

This paper presents the local mean decomposition (LMD) integrated with multi-scale permutation entropy (MPE), also known as LMD-MPE, to investigate the rolling element bearing (REB) fault diagnosis from measured vibration signals. First, the LMD decomposed the vibration data or acceleration measurement into separate product functions that are composed of both amplitude and frequency modulation. MPE then calculated the statistical permutation entropy from the product functions to extract the nonlinear features to assess and classify the condition of the healthy and damaged REB system. The comparative experimental results of the conventional LMD-based multi-scale entropy and MPE were presented to verify the authenticity of the proposed technique. The study found that LMD-MPE’s integrated approach provides reliable, damage-sensitive features when analyzing the bearing condition. The results of REB experimental datasets show that the proposed approach yields more vigorous outcomes than existing methods.

An extended continuous estimation of distribution algorithm for solving the permutation flow-shop scheduling problem

NASA Astrophysics Data System (ADS)

Shao, Zhongshi; Pi, Dechang; Shao, Weishi

2017-11-01

This article proposes an extended continuous estimation of distribution algorithm (ECEDA) to solve the permutation flow-shop scheduling problem (PFSP). In ECEDA, to make a continuous estimation of distribution algorithm (EDA) suitable for the PFSP, the largest order value rule is applied to convert continuous vectors to discrete job permutations. A probabilistic model based on a mixed Gaussian and Cauchy distribution is built to maintain the exploration ability of the EDA. Two effective local search methods, i.e. revolver-based variable neighbourhood search and Hénon chaotic-based local search, are designed and incorporated into the EDA to enhance the local exploitation. The parameters of the proposed ECEDA are calibrated by means of a design of experiments approach. Simulation results and comparisons based on some benchmark instances show the efficiency of the proposed algorithm for solving the PFSP.

Characterization of complexities in combustion instability in a lean premixed gas-turbine model combustor.

PubMed

Gotoda, Hiroshi; Amano, Masahito; Miyano, Takaya; Ikawa, Takuya; Maki, Koshiro; Tachibana, Shigeru

2012-12-01

We characterize complexities in combustion instability in a lean premixed gas-turbine model combustor by nonlinear time series analysis to evaluate permutation entropy, fractal dimensions, and short-term predictability. The dynamic behavior in combustion instability near lean blowout exhibits a self-affine structure and is ascribed to fractional Brownian motion. It undergoes chaos by the onset of combustion oscillations with slow amplitude modulation. Our results indicate that nonlinear time series analysis is capable of characterizing complexities in combustion instability close to lean blowout.

Predicting clinical diagnosis in Huntington's disease: An imaging polymarker

PubMed Central

Daws, Richard E.; Soreq, Eyal; Johnson, Eileanoir B.; Scahill, Rachael I.; Tabrizi, Sarah J.; Barker, Roger A.; Hampshire, Adam

2018-01-01

Objective Huntington's disease (HD) gene carriers can be identified before clinical diagnosis; however, statistical models for predicting when overt motor symptoms will manifest are too imprecise to be useful at the level of the individual. Perfecting this prediction is integral to the search for disease modifying therapies. This study aimed to identify an imaging marker capable of reliably predicting real‐life clinical diagnosis in HD. Method A multivariate machine learning approach was applied to resting‐state and structural magnetic resonance imaging scans from 19 premanifest HD gene carriers (preHD, 8 of whom developed clinical disease in the 5 years postscanning) and 21 healthy controls. A classification model was developed using cross‐group comparisons between preHD and controls, and within the preHD group in relation to “estimated” and “actual” proximity to disease onset. Imaging measures were modeled individually, and combined, and permutation modeling robustly tested classification accuracy. Results Classification performance for preHDs versus controls was greatest when all measures were combined. The resulting polymarker predicted converters with high accuracy, including those who were not expected to manifest in that time scale based on the currently adopted statistical models. Interpretation We propose that a holistic multivariate machine learning treatment of brain abnormalities in the premanifest phase can be used to accurately identify those patients within 5 years of developing motor features of HD, with implications for prognostication and preclinical trials. Ann Neurol 2018;83:532–543 PMID:29405351

A statistical method for the conservative adjustment of false discovery rate (q-value).

PubMed

Lai, Yinglei

2017-03-14

q-value is a widely used statistical method for estimating false discovery rate (FDR), which is a conventional significance measure in the analysis of genome-wide expression data. q-value is a random variable and it may underestimate FDR in practice. An underestimated FDR can lead to unexpected false discoveries in the follow-up validation experiments. This issue has not been well addressed in literature, especially in the situation when the permutation procedure is necessary for p-value calculation. We proposed a statistical method for the conservative adjustment of q-value. In practice, it is usually necessary to calculate p-value by a permutation procedure. This was also considered in our adjustment method. We used simulation data as well as experimental microarray or sequencing data to illustrate the usefulness of our method. The conservativeness of our approach has been mathematically confirmed in this study. We have demonstrated the importance of conservative adjustment of q-value, particularly in the situation that the proportion of differentially expressed genes is small or the overall differential expression signal is weak.

Unifying the rotational and permutation symmetry of nuclear spin states: Schur-Weyl duality in molecular physics.

PubMed

Schmiedt, Hanno; Jensen, Per; Schlemmer, Stephan

2016-08-21

In modern physics and chemistry concerned with many-body systems, one of the mainstays is identical-particle-permutation symmetry. In particular, both the intra-molecular dynamics of a single molecule and the inter-molecular dynamics associated, for example, with reactive molecular collisions are strongly affected by selection rules originating in nuclear-permutation symmetry operations being applied to the total internal wavefunctions, including nuclear spin, of the molecules involved. We propose here a general tool to determine coherently the permutation symmetry and the rotational symmetry (associated with the group of arbitrary rotations of the entire molecule in space) of molecular wavefunctions, in particular the nuclear-spin functions. Thus far, these two symmetries were believed to be mutually independent and it has even been argued that under certain circumstances, it is impossible to establish a one-to-one correspondence between them. However, using the Schur-Weyl duality theorem we show that the two types of symmetry are inherently coupled. In addition, we use the ingenious representation-theory technique of Young tableaus to represent the molecular nuclear-spin degrees of freedom in terms of well-defined mathematical objects. This simplifies the symmetry classification of the nuclear wavefunction even for large molecules. Also, the application to reactive collisions is very straightforward and provides a much simplified approach to obtaining selection rules.

Unifying the rotational and permutation symmetry of nuclear spin states: Schur-Weyl duality in molecular physics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schmiedt, Hanno; Schlemmer, Stephan; Jensen, Per, E-mail: jensen@uni-wuppertal.de

In modern physics and chemistry concerned with many-body systems, one of the mainstays is identical-particle-permutation symmetry. In particular, both the intra-molecular dynamics of a single molecule and the inter-molecular dynamics associated, for example, with reactive molecular collisions are strongly affected by selection rules originating in nuclear-permutation symmetry operations being applied to the total internal wavefunctions, including nuclear spin, of the molecules involved. We propose here a general tool to determine coherently the permutation symmetry and the rotational symmetry (associated with the group of arbitrary rotations of the entire molecule in space) of molecular wavefunctions, in particular the nuclear-spin functions. Thusmore » far, these two symmetries were believed to be mutually independent and it has even been argued that under certain circumstances, it is impossible to establish a one-to-one correspondence between them. However, using the Schur-Weyl duality theorem we show that the two types of symmetry are inherently coupled. In addition, we use the ingenious representation-theory technique of Young tableaus to represent the molecular nuclear-spin degrees of freedom in terms of well-defined mathematical objects. This simplifies the symmetry classification of the nuclear wavefunction even for large molecules. Also, the application to reactive collisions is very straightforward and provides a much simplified approach to obtaining selection rules.« less

Potential energy surface fitting by a statistically localized, permutationally invariant, local interpolating moving least squares method for the many-body potential: Method and application to N{sub 4}

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bender, Jason D.; Doraiswamy, Sriram; Candler, Graham V., E-mail: truhlar@umn.edu, E-mail: candler@aem.umn.edu

2014-02-07

Fitting potential energy surfaces to analytic forms is an important first step for efficient molecular dynamics simulations. Here, we present an improved version of the local interpolating moving least squares method (L-IMLS) for such fitting. Our method has three key improvements. First, pairwise interactions are modeled separately from many-body interactions. Second, permutational invariance is incorporated in the basis functions, using permutationally invariant polynomials in Morse variables, and in the weight functions. Third, computational cost is reduced by statistical localization, in which we statistically correlate the cutoff radius with data point density. We motivate our discussion in this paper with amore » review of global and local least-squares-based fitting methods in one dimension. Then, we develop our method in six dimensions, and we note that it allows the analytic evaluation of gradients, a feature that is important for molecular dynamics. The approach, which we call statistically localized, permutationally invariant, local interpolating moving least squares fitting of the many-body potential (SL-PI-L-IMLS-MP, or, more simply, L-IMLS-G2), is used to fit a potential energy surface to an electronic structure dataset for N{sub 4}. We discuss its performance on the dataset and give directions for further research, including applications to trajectory calculations.« less

Food habits of Arctic staghorn sculpin (Gymnocanthus tricuspis) and shorthorn sculpin (Myoxocephalus scorpius) in the northeastern Chukchi and western Beaufort Seas

NASA Astrophysics Data System (ADS)

Gray, Benjamin P.; Norcross, Brenda L.; Beaudreau, Anne H.; Blanchard, Arny L.; Seitz, Andrew C.

2017-01-01

Arctic staghorn sculpin (Gymnocanthus tricuspis) and shorthorn sculpin (Myoxocephalus scorpius) belong to Cottidae, the second most abundant fish family in the western Arctic. Although considered important in food webs, little is known about their food habits throughout this region. To address this knowledge gap, we examined and compared the diets of 515 Arctic staghorn sculpin and 422 shorthorn sculpin using stomachs collected over three summers in the northeastern Chukchi Sea (2010-2012) and one summer in the western Beaufort Sea (2011). We used permutational multivariate analysis of variance (PERMANOVA) and non-metric multidimensional scaling (nMDS) to compare sculpin diets between regions and selected size classes. Differences in mouth morphologies and predator size versus prey size relationships were examined using regression techniques. Arctic staghorn sculpin and shorthorn sculpin diet compositions differed greatly throughout the Chukchi and Beaufort Seas. Regardless of body size, the smaller-mouthed Arctic staghorn sculpin consumed mostly benthic amphipods and polychaetes, whereas the larger-mouthed shorthorn sculpin shifted from a diet composed of benthic and pelagic macroinvertebrates as smaller individuals to shrimps and fish prey as larger individuals. Within shared habitats, the sculpins appear to partition prey, either by taxa or size, in a manner that suggests no substantial overlap occurs between species. This study increases knowledge of sculpin feeding ecology in the western Arctic and offers regional, quantitative diet information that could support current and future food web modeling efforts.

A procedure to evaluate the efficiency of surface sterilization methods in culture-independent fungal endophyte studies.

PubMed

Burgdorf, R J; Laing, M D; Morris, C D; Jamal-Ally, S F

2014-01-01

Extraneous DNA interferes with PCR studies of endophytic fungi. A procedure was developed with which to evaluate the removal of extraneous DNA. Wheat (Triticum aestivum) leaves were sprayed with Saccharomyces cerevisiae and then subjected to physical and chemical surface treatments. The fungal ITS1 products were amplified from whole tissue DNA extractions. ANOVA was performed on the DNA bands representing S. cerevisiae on the agarose gel. Band profile comparisons using permutational multivariate ANOVA (PERMANOVA) and non-metric multidimensional scaling (NMDS) were performed on DGGE gel data, and band numbers were compared between treatments. Leaf surfaces were viewed under variable pressure scanning electron microscopy (VPSEM). Yeast band analysis of the agarose gel showed that there was no significant difference in the mean band DNA quantity after physical and chemical treatments, but they both differed significantly (p < 0.05) from the untreated control. PERMANOVA revealed a significant difference between all treatments (p < 0.05). The mean similarity matrix showed that the physical treatment results were more reproducible than those from the chemical treatment results. The NMDS showed that the physical treatment was the most consistent. VPSEM indicated that the physical treatment was the most effective treatment to remove surface microbes and debris. The use of molecular and microscopy methods for the post-treatment detection of yeast inoculated onto wheat leaf surfaces demonstrated the effectiveness of the surface treatment employed, and this can assist researchers in optimizing their surface sterilization techniques in DNA-based fungal endophyte studies.

Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA.

PubMed

Kelly, Brendan J; Gross, Robert; Bittinger, Kyle; Sherrill-Mix, Scott; Lewis, James D; Collman, Ronald G; Bushman, Frederic D; Li, Hongzhe

2015-08-01

The variation in community composition between microbiome samples, termed beta diversity, can be measured by pairwise distance based on either presence-absence or quantitative species abundance data. PERMANOVA, a permutation-based extension of multivariate analysis of variance to a matrix of pairwise distances, partitions within-group and between-group distances to permit assessment of the effect of an exposure or intervention (grouping factor) upon the sampled microbiome. Within-group distance and exposure/intervention effect size must be accurately modeled to estimate statistical power for a microbiome study that will be analyzed with pairwise distances and PERMANOVA. We present a framework for PERMANOVA power estimation tailored to marker-gene microbiome studies that will be analyzed by pairwise distances, which includes: (i) a novel method for distance matrix simulation that permits modeling of within-group pairwise distances according to pre-specified population parameters; (ii) a method to incorporate effects of different sizes within the simulated distance matrix; (iii) a simulation-based method for estimating PERMANOVA power from simulated distance matrices; and (iv) an R statistical software package that implements the above. Matrices of pairwise distances can be efficiently simulated to satisfy the triangle inequality and incorporate group-level effects, which are quantified by the adjusted coefficient of determination, omega-squared (ω2). From simulated distance matrices, available PERMANOVA power or necessary sample size can be estimated for a planned microbiome study. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A procedure to evaluate the efficiency of surface sterilization methods in culture-independent fungal endophyte studies

PubMed Central

Burgdorf, R.J.; Laing, M.D.; Morris, C.D.; Jamal-Ally, S.F.

2014-01-01

Extraneous DNA interferes with PCR studies of endophytic fungi. A procedure was developed with which to evaluate the removal of extraneous DNA. Wheat (Triticum aestivum) leaves were sprayed with Saccharomyces cerevisiae and then subjected to physical and chemical surface treatments. The fungal ITS1 products were amplified from whole tissue DNA extractions. ANOVA was performed on the DNA bands representing S. cerevisiae on the agarose gel. Band profile comparisons using permutational multivariate ANOVA (PERMANOVA) and non-metric multidimensional scaling (NMDS) were performed on DGGE gel data, and band numbers were compared between treatments. Leaf surfaces were viewed under variable pressure scanning electron microscopy (VPSEM). Yeast band analysis of the agarose gel showed that there was no significant difference in the mean band DNA quantity after physical and chemical treatments, but they both differed significantly (p < 0.05) from the untreated control. PERMANOVA revealed a significant difference between all treatments (p < 0.05). The mean similarity matrix showed that the physical treatment results were more reproducible than those from the chemical treatment results. The NMDS showed that the physical treatment was the most consistent. VPSEM indicated that the physical treatment was the most effective treatment to remove surface microbes and debris. The use of molecular and microscopy methods for the post-treatment detection of yeast inoculated onto wheat leaf surfaces demonstrated the effectiveness of the surface treatment employed, and this can assist researchers in optimizing their surface sterilization techniques in DNA-based fungal endophyte studies. PMID:25477934

Gut Microbial Diversity in Women With Polycystic Ovary Syndrome Correlates With Hyperandrogenism.

PubMed

Torres, Pedro J; Siakowska, Martyna; Banaszewska, Beata; Pawelczyk, Leszek; Duleba, Antoni J; Kelley, Scott T; Thackray, Varykina G

2018-04-01

A majority of women with polycystic ovary syndrome (PCOS) have metabolic abnormalities that result in an increased risk of developing type 2 diabetes and heart disease. Correlative studies have shown an association between changes in the gut microbiome and metabolic disorders. Two recent studies reported a decrease in α diversity of the gut microbiome in women with PCOS compared with healthy women. We investigated whether changes in the gut microbiome correlated with specific clinical parameters in women with PCOS compared with healthy women. We also investigated whether there were changes in the gut microbiome in women with polycystic ovarian morphology (PCOM) who lacked the other diagnostic criteria of PCOS. Subjects were recruited at the Poznan University of Medical Sciences. Fecal microbial diversity profiles of healthy women (n = 48), women with PCOM (n = 42), and women diagnosed with PCOS using the Rotterdam criteria (n = 73) were analyzed using 16S ribosomal RNA gene sequencing. Lower α diversity was observed in women with PCOS compared with healthy women. Women with PCOM had a change in α diversity that was intermediate between that of the other two groups. Regression analyses showed that hyperandrogenism, total testosterone, and hirsutism were negatively correlated with α diversity. Permutational multivariate analysis of variance in UniFrac distances showed that hyperandrogenism was also correlated with β diversity. A random forest identified bacteria that discriminated between healthy women and women with PCOS. These results suggest that hyperandrogenism may play a critical role in altering the gut microbiome in women with PCOS.

Male circumcision significantly reduces prevalence and load of genital anaerobic bacteria.

PubMed

Liu, Cindy M; Hungate, Bruce A; Tobian, Aaron A R; Serwadda, David; Ravel, Jacques; Lester, Richard; Kigozi, Godfrey; Aziz, Maliha; Galiwango, Ronald M; Nalugoda, Fred; Contente-Cuomo, Tania L; Wawer, Maria J; Keim, Paul; Gray, Ronald H; Price, Lance B

2013-04-16

Male circumcision reduces female-to-male HIV transmission. Hypothesized mechanisms for this protective effect include decreased HIV target cell recruitment and activation due to changes in the penis microbiome. We compared the coronal sulcus microbiota of men from a group of uncircumcised controls (n = 77) and from a circumcised intervention group (n = 79) at enrollment and year 1 follow-up in a randomized circumcision trial in Rakai, Uganda. We characterized microbiota using16S rRNA gene-based quantitative PCR (qPCR) and pyrosequencing, log response ratio (LRR), Bayesian classification, nonmetric multidimensional scaling (nMDS), and permutational multivariate analysis of variance (PerMANOVA). At baseline, men in both study arms had comparable coronal sulcus microbiota; however, by year 1, circumcision decreased the total bacterial load and reduced microbiota biodiversity. Specifically, the prevalence and absolute abundance of 12 anaerobic bacterial taxa decreased significantly in the circumcised men. While aerobic bacterial taxa also increased postcircumcision, these gains were minor. The reduction in anaerobes may partly account for the effects of circumcision on reduced HIV acquisition. The bacterial changes identified in this study may play an important role in the HIV risk reduction conferred by male circumcision. Decreasing the load of specific anaerobes could reduce HIV target cell recruitment to the foreskin. Understanding the mechanisms that underlie the benefits of male circumcision could help to identify new intervention strategies for decreasing HIV transmission, applicable to populations with high HIV prevalence where male circumcision is culturally less acceptable.

Soil Bacteria and Fungi Respond on Different Spatial Scales to Invasion by the Legume Lespedeza cuneata.

PubMed

Yannarell, Anthony C; Busby, Ryan R; Denight, Michael L; Gebhart, Dick L; Taylor, Steven J

2011-01-01

The spatial scale on which microbial communities respond to plant invasions may provide important clues as to the nature of potential invader-microbe interactions. Lespedeza cuneata (Dum. Cours.) G. Don is an invasive legume that may benefit from associations with mycorrhizal fungi; however, it has also been suggested that the plant is allelopathic and may alter the soil chemistry of invaded sites through secondary metabolites in its root exudates or litter. Thus, L. cuneata invasion may interact with soil microorganisms on a variety of scales. We investigated L. cuneata-related changes to soil bacterial and fungal communities at two spatial scales using multiple sites from across its invaded N. American range. Using whole-community DNA fingerprinting, we characterized microbial community variation at the scale of entire invaded sites and at the scale of individual plants. Based on permutational multivariate analysis of variance, soil bacterial communities in heavily invaded sites were significantly different from those of uninvaded sites, but bacteria did not show any evidence of responding at very local scales around individual plants. In contrast, soil fungi did not change significantly at the scale of entire sites, but there were significant differences between fungal communities of native versus exotic plants within particular sites. The differential scaling of bacterial and fungal responses indicates that L. cuneata interacts differently with soil bacteria and soil fungi, and these microorganisms may play very different roles in the invasion process of this plant.

Evaluation of bloodstream infections, Clostridium difficile infections, and gut microbiota in pediatric oncology patients.

PubMed

Nycz, Bryan T; Dominguez, Samuel R; Friedman, Deborah; Hilden, Joanne M; Ir, Diana; Robertson, Charles E; Frank, Daniel N

2018-01-01

Bloodstream infections (BSI) and Clostridium difficile infections (CDI) in pediatric oncology/hematology/bone marrow transplant (BMT) populations are associated with significant morbidity and mortality. The objective of this study was to explore possible associations between altered microbiome composition and the occurrence of BSI and CDI in a cohort of pediatric oncology patients. Stool samples were collected from all patients admitted to the pediatric oncology floor from Oct.-Dec. 2012. Bacterial profiles from patient stools were determined by bacterial 16S rRNA gene profiling. Differences in overall microbiome composition were assessed by a permutation-based multivariate analysis of variance test, while differences in the relative abundances of specific taxa were assessed by Kruskal-Wallis tests. At admission, 9 of 42 patients (21%) were colonized with C. difficile, while 6 of 42 (14%) subsequently developed a CDI. Furthermore, 3 patients (7%) previously had a BSI and 6 patients (14%) subsequently developed a BSI. Differences in overall microbiome composition were significantly associated with disease type (p = 0.0086), chemotherapy treatment (p = 0.018), BSI following admission from any cause (p < 0.0001) or suspected gastrointestinal organisms (p = 0.00043). No differences in baseline microbiota were observed between individuals who did or did not subsequently develop C. difficile infection. Additionally, multiple bacterial groups varied significantly between subjects with post-admission BSI compared with no BSI. Our results suggest that differences in gut microbiota not only are associated with type of cancer and chemotherapy, but may also be predictive of subsequent bloodstream infection.

A prognostic classifier for patients with colorectal cancer liver metastasis, based on AURKA, PTGS2 and MMP9.

PubMed

Goos, Jeroen A C M; Coupé, Veerle M H; van de Wiel, Mark A; Diosdado, Begoña; Delis-Van Diemen, Pien M; Hiemstra, Annemieke C; de Cuba, Erienne M V; Beliën, Jeroen A M; Menke-van der Houven van Oordt, C Willemien; Geldof, Albert A; Meijer, Gerrit A; Hoekstra, Otto S; Fijneman, Remond J A

2016-01-12

Prognosis of patients with colorectal cancer liver metastasis (CRCLM) is estimated based on clinicopathological models. Stratifying patients based on tumor biology may have additional value. Tissue micro-arrays (TMAs), containing resected CRCLM and corresponding primary tumors from a multi-institutional cohort of 507 patients, were immunohistochemically stained for 18 candidate biomarkers. Cross-validated hazard rate ratios (HRRs) for overall survival (OS) and the proportion of HRRs with opposite effect (P(HRR < 1) or P(HRR > 1)) were calculated. A classifier was constructed by classification and regression tree (CART) analysis and its prognostic value determined by permutation analysis. Correlations between protein expression in primary tumor-CRCLM pairs were calculated. Based on their putative prognostic value, EGFR (P(HRR < 1) = .02), AURKA (P(HRR < 1) = .02), VEGFA (P(HRR < 1) = .02), PTGS2 (P(HRR < 1) = .01), SLC2A1 (P(HRR > 1) < 01), HIF1α (P(HRR > 1) = .06), KCNQ1 (P(HRR > 1) = .09), CEA (P (HRR > 1) = .05) and MMP9 (P(HRR < 1) = .07) were included in the CART analysis (n = 201). The resulting classifier was based on AURKA, PTGS2 and MMP9 expression and was associated with OS (HRR 2.79, p < .001), also after multivariate analysis (HRR 3.57, p < .001). The prognostic value of the biomarker-based classifier was superior to the clinicopathological model (p = .001). Prognostic value was highest for colon cancer patients (HRR 5.71, p < .001) and patients not treated with systemic therapy (HRR 3.48, p < .01). Classification based on protein expression in primary tumors could be based on AURKA expression only (HRR 2.59, p = .04). A classifier was generated for patients with CRCLM with improved prognostic value compared to the standard clinicopathological prognostic parameters, which may aid selection of patients who may benefit from adjuvant systemic therapy.

Variation in the macrofaunal community over large temporal and spatial scales in the southern Yellow Sea

NASA Astrophysics Data System (ADS)

Xu, Yong; Sui, Jixing; Yang, Mei; Sun, Yue; Li, Xinzheng; Wang, Hongfa; Zhang, Baolin

2017-09-01

To detect large, temporal- and spatial-scale variations in the macrofaunal community in the southern Yellow Sea, data collected along the western, middle and eastern regions of the southern Yellow Sea from 1958 to 2014 were organized and analyzed. Statistical methods such as cluster analysis, non-metric multidimensional scaling ordination (nMDS), permutational multivariate analysis of variance (PERMANOVA), redundancy analysis (RDA) and canonical correspondence analysis (CCA) were applied. The abundance of polychaetes increased in the western region but decreased in the eastern region from 1958 to 2014, whereas the abundance of echinoderms showed an opposite trend. For the entire macrofaunal community, Margalef's richness (d), the Shannon-Wiener index (H‧) and Pielou's evenness (J‧) were significantly lower in the eastern region when compared with the other two regions. No significant temporal differences were found for d and H‧, but there were significantly lower values of J‧ in 2014. Considerable variation in the macrofaunal community structure over the past several decades and among the geographical regions at the species, genus and family levels were observed. The species, genera and families that contributed to the temporal variation in each region were also identified. The most conspicuous pattern was the increase in the species Ophiura sarsii vadicola in the eastern region. In the western region, five polychaetes (Ninoe palmata, Notomastus latericeus, Paralacydonia paradoxa, Paraprionospio pinnata and Sternaspis scutata) increased consistently from 1958 to 2014. The dominance curves showed that both the species diversity and the dominance patterns were relatively stable in the western and middle regions. Environmental parameters such as depth, temperature and salinity could only partially explain the observed biological variation in the southern Yellow Sea. Anthropogenic activities such as demersal fishing and other unmeasured environmental variables may be more responsible for the long-term changes in the macrofaunal community.

Changes in composition, ecology and structure of high-mountain vegetation: a re-visitation study over 42 years.

PubMed

Evangelista, Alberto; Frate, Ludovico; Carranza, Maria Laura; Attorre, Fabio; Pelino, Giovanni; Stanisci, Angela

2016-01-27

High-mountain ecosystems are increasingly threatened by climate change, causing biodiversity loss, habitat degradation and landscape modifications. However, very few detailed studies have focussed on plant biodiversity in the high mountains of the Mediterranean. In this study, we investigated the long-term changes that have occurred in the composition, structure and ecology of high-mountain vegetation in the central Apennines (Majella) over the last 42 years. We performed a re-visitation study, using historical and newly collected vegetation data to explore which ecological and structural features have been the most successful in coping with climatic changes. Vegetation changes were analysed by comparing geo-referenced phytosociological relevés collected in high-mountain habitats (dolines, gentle slopes and ridges) on the Majella massif in 1972 and in 2014. Composition analysis was performed by detrended correspondence analysis, followed by an analysis of similarities for statistical significance assessment and by similarity percentage procedure (SIMPER) for identifying which species indicate temporal changes. Changes in ecological and structural indicators were analysed by a permutational multivariate analysis of variance, followed by a post hoc comparison. Over the last 42 years, clear floristic changes and significant ecological and structural variations occurred. We observed a significant increase in the thermophilic and mesonitrophilic plant species and an increment in the frequencies of hemicryptophytes. This re-visitation study in the Apennines agrees with observations in other alpine ecosystems, providing new insights for a better understanding of the effects of global change on Mediterranean high-mountain biodiversity. The observed changes in floristic composition, the thermophilization process and the shift towards a more nutrient-demanding vegetation are likely attributable to the combined effect of higher temperatures and the increase in soil nutrients triggered by global change. The re-visitation approach adopted herein represents a powerful tool for studying climate-related changes in sensitive high-mountain habitats. Published by Oxford University Press on behalf of the Annals of Botany Company.

Hydrocarbon profiles throughout adult Calliphoridae aging: A promising tool for forensic entomology.

PubMed

Pechal, Jennifer L; Moore, Hannah; Drijfhout, Falko; Benbow, M Eric

2014-12-01

Blow flies (Diptera: Calliphoridae) are typically the first insects to arrive at human remains and carrion. Predictable succession patterns and known larval development of necrophagous insects on vertebrate remains can assist a forensic entomologist with estimates of a minimum post-mortem interval (PMImin) range. However, adult blow flies are infrequently used to estimate the PMImin, but rather are used for a confirmation of larval species identification. Cuticular hydrocarbons have demonstrated potential for estimating adult blow fly age, as hydrocarbons are present throughout blow fly development, from egg to adult, and are stable structures. The goal of this study was to identify hydrocarbon profiles associated with the adults of a North American native blow fly species, Cochliomyia macellaria (Fabricius) and a North American invasive species, Chrysomya rufifacies (Macquart). Flies were reared at a constant temperature (25°C), a photoperiod of 14:10 (L:D) (h), and were provided water, sugar and powdered milk ad libitum. Ten adult females from each species were collected at day 1, 5, 10, 20, and 30 post-emergence. Hydrocarbon compounds were extracted and then identified using gas chromatography-mass spectrometry (GC-MS) analysis. A total of 37 and 35 compounds were detected from C. macellaria and Ch. rufifacies, respectively. There were 24 and 23 n-alkene and methyl-branched alkane hydrocarbons from C. macellaria and Ch. rufifacies, respectively (10 compounds were shared between species), used for statistical analysis. Non-metric multidimensional scaling analysis and permutational multivariate analysis of variance were used to analyze the hydrocarbon profiles with significant differences (P<0.001) detected among post-emergence age cohorts for each species, and unique hydrocarbon profiles detected as each adult blow fly species aged. This work provides empirical data that serve as a foundation for future research into improving PMImin estimates made by forensic practitioners and potentially increase the use of adult insects during death investigations. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Brain Computation Is Organized via Power-of-Two-Based Permutation Logic.

PubMed

Xie, Kun; Fox, Grace E; Liu, Jun; Lyu, Cheng; Lee, Jason C; Kuang, Hui; Jacobs, Stephanie; Li, Meng; Liu, Tianming; Song, Sen; Tsien, Joe Z

2016-01-01

There is considerable scientific interest in understanding how cell assemblies-the long-presumed computational motif-are organized so that the brain can generate intelligent cognition and flexible behavior. The Theory of Connectivity proposes that the origin of intelligence is rooted in a power-of-two-based permutation logic ( N = 2 i -1), producing specific-to-general cell-assembly architecture capable of generating specific perceptions and memories, as well as generalized knowledge and flexible actions. We show that this power-of-two-based permutation logic is widely used in cortical and subcortical circuits across animal species and is conserved for the processing of a variety of cognitive modalities including appetitive, emotional and social information. However, modulatory neurons, such as dopaminergic (DA) neurons, use a simpler logic despite their distinct subtypes. Interestingly, this specific-to-general permutation logic remained largely intact although NMDA receptors-the synaptic switch for learning and memory-were deleted throughout adulthood, suggesting that the logic is developmentally pre-configured. Moreover, this computational logic is implemented in the cortex via combining a random-connectivity strategy in superficial layers 2/3 with nonrandom organizations in deep layers 5/6. This randomness of layers 2/3 cliques-which preferentially encode specific and low-combinatorial features and project inter-cortically-is ideal for maximizing cross-modality novel pattern-extraction, pattern-discrimination and pattern-categorization using sparse code, consequently explaining why it requires hippocampal offline-consolidation. In contrast, the nonrandomness in layers 5/6-which consists of few specific cliques but a higher portion of more general cliques projecting mostly to subcortical systems-is ideal for feedback-control of motivation, emotion, consciousness and behaviors. These observations suggest that the brain's basic computational algorithm is indeed organized by the power-of-two-based permutation logic. This simple mathematical logic can account for brain computation across the entire evolutionary spectrum, ranging from the simplest neural networks to the most complex.

Brain Computation Is Organized via Power-of-Two-Based Permutation Logic

PubMed Central

Xie, Kun; Fox, Grace E.; Liu, Jun; Lyu, Cheng; Lee, Jason C.; Kuang, Hui; Jacobs, Stephanie; Li, Meng; Liu, Tianming; Song, Sen; Tsien, Joe Z.

2016-01-01

There is considerable scientific interest in understanding how cell assemblies—the long-presumed computational motif—are organized so that the brain can generate intelligent cognition and flexible behavior. The Theory of Connectivity proposes that the origin of intelligence is rooted in a power-of-two-based permutation logic (N = 2i–1), producing specific-to-general cell-assembly architecture capable of generating specific perceptions and memories, as well as generalized knowledge and flexible actions. We show that this power-of-two-based permutation logic is widely used in cortical and subcortical circuits across animal species and is conserved for the processing of a variety of cognitive modalities including appetitive, emotional and social information. However, modulatory neurons, such as dopaminergic (DA) neurons, use a simpler logic despite their distinct subtypes. Interestingly, this specific-to-general permutation logic remained largely intact although NMDA receptors—the synaptic switch for learning and memory—were deleted throughout adulthood, suggesting that the logic is developmentally pre-configured. Moreover, this computational logic is implemented in the cortex via combining a random-connectivity strategy in superficial layers 2/3 with nonrandom organizations in deep layers 5/6. This randomness of layers 2/3 cliques—which preferentially encode specific and low-combinatorial features and project inter-cortically—is ideal for maximizing cross-modality novel pattern-extraction, pattern-discrimination and pattern-categorization using sparse code, consequently explaining why it requires hippocampal offline-consolidation. In contrast, the nonrandomness in layers 5/6—which consists of few specific cliques but a higher portion of more general cliques projecting mostly to subcortical systems—is ideal for feedback-control of motivation, emotion, consciousness and behaviors. These observations suggest that the brain’s basic computational algorithm is indeed organized by the power-of-two-based permutation logic. This simple mathematical logic can account for brain computation across the entire evolutionary spectrum, ranging from the simplest neural networks to the most complex. PMID:27895562

PERMANOVA-S: association test for microbial community composition that accommodates confounders and multiple distances.

PubMed

Tang, Zheng-Zheng; Chen, Guanhua; Alekseyenko, Alexander V

2016-09-01

Recent advances in sequencing technology have made it possible to obtain high-throughput data on the composition of microbial communities and to study the effects of dysbiosis on the human host. Analysis of pairwise intersample distances quantifies the association between the microbiome diversity and covariates of interest (e.g. environmental factors, clinical outcomes, treatment groups). In the design of these analyses, multiple choices for distance metrics are available. Most distance-based methods, however, use a single distance and are underpowered if the distance is poorly chosen. In addition, distance-based tests cannot flexibly handle confounding variables, which can result in excessive false-positive findings. We derive presence-weighted UniFrac to complement the existing UniFrac distances for more powerful detection of the variation in species richness. We develop PERMANOVA-S, a new distance-based method that tests the association of microbiome composition with any covariates of interest. PERMANOVA-S improves the commonly-used Permutation Multivariate Analysis of Variance (PERMANOVA) test by allowing flexible confounder adjustments and ensembling multiple distances. We conducted extensive simulation studies to evaluate the performance of different distances under various patterns of association. Our simulation studies demonstrate that the power of the test relies on how well the selected distance captures the nature of the association. The PERMANOVA-S unified test combines multiple distances and achieves good power regardless of the patterns of the underlying association. We demonstrate the usefulness of our approach by reanalyzing several real microbiome datasets. miProfile software is freely available at https://medschool.vanderbilt.edu/tang-lab/software/miProfile z.tang@vanderbilt.edu or g.chen@vanderbilt.edu Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

PERMANOVA-S: association test for microbial community composition that accommodates confounders and multiple distances

PubMed Central

Tang, Zheng-Zheng; Chen, Guanhua; Alekseyenko, Alexander V.

2016-01-01

Motivation: Recent advances in sequencing technology have made it possible to obtain high-throughput data on the composition of microbial communities and to study the effects of dysbiosis on the human host. Analysis of pairwise intersample distances quantifies the association between the microbiome diversity and covariates of interest (e.g. environmental factors, clinical outcomes, treatment groups). In the design of these analyses, multiple choices for distance metrics are available. Most distance-based methods, however, use a single distance and are underpowered if the distance is poorly chosen. In addition, distance-based tests cannot flexibly handle confounding variables, which can result in excessive false-positive findings. Results: We derive presence-weighted UniFrac to complement the existing UniFrac distances for more powerful detection of the variation in species richness. We develop PERMANOVA-S, a new distance-based method that tests the association of microbiome composition with any covariates of interest. PERMANOVA-S improves the commonly-used Permutation Multivariate Analysis of Variance (PERMANOVA) test by allowing flexible confounder adjustments and ensembling multiple distances. We conducted extensive simulation studies to evaluate the performance of different distances under various patterns of association. Our simulation studies demonstrate that the power of the test relies on how well the selected distance captures the nature of the association. The PERMANOVA-S unified test combines multiple distances and achieves good power regardless of the patterns of the underlying association. We demonstrate the usefulness of our approach by reanalyzing several real microbiome datasets. Availability and Implementation: miProfile software is freely available at https://medschool.vanderbilt.edu/tang-lab/software/miProfile. Contact: z.tang@vanderbilt.edu or g.chen@vanderbilt.edu Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27197815

Bolus Weekly Vitamin D3 Supplementation Impacts Gut and Airway Microbiota in Adults With Cystic Fibrosis: A Double-Blind, Randomized, Placebo-Controlled Clinical Trial.

PubMed

Kanhere, Mansi; He, Jiabei; Chassaing, Benoit; Ziegler, Thomas R; Alvarez, Jessica A; Ivie, Elizabeth A; Hao, Li; Hanfelt, John; Gewirtz, Andrew T; Tangpricha, Vin

2018-02-01

Disruption of gut microbiota may exacerbate severity of cystic fibrosis (CF). Vitamin D deficiency is a common comorbidity in patients with CF that may influence composition of the gut microbiota. Compare microbiota of vitamin D-sufficient and -insufficient CF patients and assess impact of a weekly high-dose vitamin D3 bolus regimen on gut and airway microbiome in adults with CF and vitamin D insufficiency (25-hydroxyvitamin D < 30 ng/mL). Forty-one subjects with CF were classified into two groups: vitamin D insufficient (n = 23) and vitamin D sufficient (n = 18). Subjects with vitamin D insufficiency were randomized to receive 50,000 IU of oral vitamin D3 or placebo weekly for 12 weeks. Sputum and stool samples were obtained pre- and postintervention and 16S ribosomal RNA genes sequenced using Illumina MiSeq technology. Gut microbiota differed significantly based on vitamin D status with Gammaproteobacteria, which contain numerous, potentially pathogenic species enriched in the vitamin D-insufficient group. Principal coordinates analysis showed differential gut microbiota composition within the vitamin D-insufficient patients following 12 weeks treatment with placebo or vitamin D3 (permutation multivariate analysis of variance = 0.024), with Lactococcus significantly enriched in subjects treated with vitamin D3, whereas Veillonella and Erysipelotrichaceae were significantly enriched in patients treated with placebo. This exploratory study suggests that vitamin D insufficiency is associated with alterations in microbiota composition that may promote inflammation and that supplementation with vitamin D has the potential to impact microbiota composition. Additional studies to determine the impact of vitamin D on microbiota benefit clinical outcomes in CF are warranted. Copyright © 2017 Endocrine Society

Search for Microorganisms in Men with Urologic Chronic Pelvic Pain Syndrome: A Culture-Independent Analysis in the MAPP Research Network

PubMed Central

Nickel, J. Curtis; Stephens, Alisa; Landis, J. Richard; Chen, Jun; Mullins, Chris; van Bokhoven, Adrie; Lucia, M. Scott; Melton-Kreft, Rachael; Ehrlich, Garth D.

2015-01-01

Introduction We used next-generation, state-of-the-art, culture-independent methodology to survey urine microbiota of UCPPS males and control participants enrolled in the MAPP Network to investigate a possible microbial etiology. Methods Male UCPPS patients and matched controls were asked to provide VB1, VB2 and VB3 urine specimens. Specimens were analyzed with Ibis T-5000 Universal Biosensor technology to provide comprehensive identification of bacterial and select fungal species. Differences between UCPPS and control study participants for presence of species or species variation within a higher taxonomic grouping (genus) were evaluated using permutational multivariate analysis of variance and logistic regression. Results VB1 and VB2 urine specimens were obtained from 110 (VB3 in 67) UCPPS participants and 115 (VB3 in 62) controls. A total of 78, 73 and 54 species (42, 39 and 27 genera) were detected in VB1, VB2 and VB3 respectively. Mean (SD) VB1, VB2 and VB3 species count per person was 1.62 (1.28), 1.38 (1.36) and 1.33(1.24) for cases and 1.75(1.32), 1.23(1.15) and 1.56 (0.97) for controls respectively. Overall species and genus composition differed significantly between UCPPS and control participants in VB1 (p=0.002 species level, p=0.004 genus level) with Burkholderia cenocepacia over represented in UCPPS cases. No significant differences were observed at any level in VB2 or VB3 samples. Conclusions Assessment of baseline culture-independent microbiological data from male subjects enrolled in the MAPP Network has identified over representation of B cenocepacia in UCPPS. Future studies are planned to further evaluate microbiota associations with variable and changing UCPPS symptom patterns. PMID:25596358

Successful attack on permutation-parity-machine-based neural cryptography.

PubMed

Seoane, Luís F; Ruttor, Andreas

2012-02-01

An algorithm is presented which implements a probabilistic attack on the key-exchange protocol based on permutation parity machines. Instead of imitating the synchronization of the communicating partners, the strategy consists of a Monte Carlo method to sample the space of possible weights during inner rounds and an analytic approach to convey the extracted information from one outer round to the next one. The results show that the protocol under attack fails to synchronize faster than an eavesdropper using this algorithm.

Crossbar Switches For Optical Data-Communication Networks

NASA Technical Reports Server (NTRS)

Monacos, Steve P.

1994-01-01

Optoelectronic and electro-optical crossbar switches called "permutation engines" (PE's) developed to route packets of data through fiber-optic communication networks. Basic network concept described in "High-Speed Optical Wide-Area Data-Communication Network" (NPO-18983). Nonblocking operation achieved by decentralized switching and control scheme. Each packet routed up or down in each column of this 5-input/5-output permutation engine. Routing algorithm ensures each packet arrives at its designated output port without blocking any other packet that does not contend for same output port.

Security of the Five-Round KASUMI Type Permutation

NASA Astrophysics Data System (ADS)

Iwata, Tetsu; Yagi, Tohru; Kurosawa, Kaoru

KASUMI is a blockcipher that forms the heart of the 3GPP confidentiality and integrity algorithms. In this paper, we study the security of the five-round KASUMI type permutations, and derive a highly non-trivial security bound against adversaries with adaptive chosen plaintext and chosen ciphertext attacks. To derive our security bound, we heavily use the tools from graph theory. However the result does not show its super-pseudorandomness, this gives us a strong evidence that the design of KASUMI is sound.

A note on the estimation of the Pareto efficient set for multiobjective matrix permutation problems.

PubMed

Brusco, Michael J; Steinley, Douglas

2012-02-01

There are a number of important problems in quantitative psychology that require the identification of a permutation of the n rows and columns of an n × n proximity matrix. These problems encompass applications such as unidimensional scaling, paired-comparison ranking, and anti-Robinson forms. The importance of simultaneously incorporating multiple objective criteria in matrix permutation applications is well recognized in the literature; however, to date, there has been a reliance on weighted-sum approaches that transform the multiobjective problem into a single-objective optimization problem. Although exact solutions to these single-objective problems produce supported Pareto efficient solutions to the multiobjective problem, many interesting unsupported Pareto efficient solutions may be missed. We illustrate the limitation of the weighted-sum approach with an example from the psychological literature and devise an effective heuristic algorithm for estimating both the supported and unsupported solutions of the Pareto efficient set. © 2011 The British Psychological Society.

Automated matching of corresponding seed images of three simulator radiographs to allow 3D triangulation of implanted seeds.

PubMed

Altschuler, M D; Kassaee, A

1997-02-01

To match corresponding seed images in different radiographs so that the 3D seed locations can be triangulated automatically and without ambiguity requires (at least) three radiographs taken from different perspectives, and an algorithm that finds the proper permutations of the seed-image indices. Matching corresponding images in only two radiographs introduces inherent ambiguities which can be resolved only with the use of non-positional information obtained with intensive human effort. Matching images in three or more radiographs is an 'NP (Non-determinant in Polynomial time)-complete' problem. Although the matching problem is fundamental, current methods for three-radiograph seed-image matching use 'local' (seed-by-seed) methods that may lead to incorrect matchings. We describe a permutation-sampling method which not only gives good 'global' (full permutation) matches for the NP-complete three-radiograph seed-matching problem, but also determines the reliability of the radiographic data themselves, namely, whether the patient moved in the interval between radiographic perspectives.

Automated matching of corresponding seed images of three simulator radiographs to allow 3D triangulation of implanted seeds

NASA Astrophysics Data System (ADS)

Altschuler, Martin D.; Kassaee, Alireza

1997-02-01

To match corresponding seed images in different radiographs so that the 3D seed locations can be triangulated automatically and without ambiguity requires (at least) three radiographs taken from different perspectives, and an algorithm that finds the proper permutations of the seed-image indices. Matching corresponding images in only two radiographs introduces inherent ambiguities which can be resolved only with the use of non-positional information obtained with intensive human effort. Matching images in three or more radiographs is an `NP (Non-determinant in Polynomial time)-complete' problem. Although the matching problem is fundamental, current methods for three-radiograph seed-image matching use `local' (seed-by-seed) methods that may lead to incorrect matchings. We describe a permutation-sampling method which not only gives good `global' (full permutation) matches for the NP-complete three-radiograph seed-matching problem, but also determines the reliability of the radiographic data themselves, namely, whether the patient moved in the interval between radiographic perspectives.

Classifying epileptic EEG signals with delay permutation entropy and Multi-Scale K-means.

PubMed

Zhu, Guohun; Li, Yan; Wen, Peng Paul; Wang, Shuaifang

2015-01-01

Most epileptic EEG classification algorithms are supervised and require large training datasets, that hinder their use in real time applications. This chapter proposes an unsupervised Multi-Scale K-means (MSK-means) MSK-means algorithm to distinguish epileptic EEG signals and identify epileptic zones. The random initialization of the K-means algorithm can lead to wrong clusters. Based on the characteristics of EEGs, the MSK-means MSK-means algorithm initializes the coarse-scale centroid of a cluster with a suitable scale factor. In this chapter, the MSK-means algorithm is proved theoretically superior to the K-means algorithm on efficiency. In addition, three classifiers: the K-means, MSK-means MSK-means and support vector machine (SVM), are used to identify seizure and localize epileptogenic zone using delay permutation entropy features. The experimental results demonstrate that identifying seizure with the MSK-means algorithm and delay permutation entropy achieves 4. 7 % higher accuracy than that of K-means, and 0. 7 % higher accuracy than that of the SVM.

Exploiting Lipid Permutation Symmetry to Compute Membrane Remodeling Free Energies.

PubMed

Bubnis, Greg; Risselada, Herre Jelger; Grubmüller, Helmut

2016-10-28

A complete physical description of membrane remodeling processes, such as fusion or fission, requires knowledge of the underlying free energy landscapes, particularly in barrier regions involving collective shape changes, topological transitions, and high curvature, where Canham-Helfrich (CH) continuum descriptions may fail. To calculate these free energies using atomistic simulations, one must address not only the sampling problem due to high free energy barriers, but also an orthogonal sampling problem of combinatorial complexity stemming from the permutation symmetry of identical lipids. Here, we solve the combinatorial problem with a permutation reduction scheme to map a structural ensemble into a compact, nondegenerate subregion of configuration space, thereby permitting straightforward free energy calculations via umbrella sampling. We applied this approach, using a coarse-grained lipid model, to test the CH description of bending and found sharp increases in the bending modulus for curvature radii below 10 nm. These deviations suggest that an anharmonic bending term may be required for CH models to give quantitative energetics of highly curved states.

A fast chaos-based image encryption scheme with a dynamic state variables selection mechanism

NASA Astrophysics Data System (ADS)

Chen, Jun-xin; Zhu, Zhi-liang; Fu, Chong; Yu, Hai; Zhang, Li-bo

2015-03-01

In recent years, a variety of chaos-based image cryptosystems have been investigated to meet the increasing demand for real-time secure image transmission. Most of them are based on permutation-diffusion architecture, in which permutation and diffusion are two independent procedures with fixed control parameters. This property results in two flaws. (1) At least two chaotic state variables are required for encrypting one plain pixel, in permutation and diffusion stages respectively. Chaotic state variables produced with high computation complexity are not sufficiently used. (2) The key stream solely depends on the secret key, and hence the cryptosystem is vulnerable against known/chosen-plaintext attacks. In this paper, a fast chaos-based image encryption scheme with a dynamic state variables selection mechanism is proposed to enhance the security and promote the efficiency of chaos-based image cryptosystems. Experimental simulations and extensive cryptanalysis have been carried out and the results prove the superior security and high efficiency of the scheme.

Simultaneous and Sequential MS/MS Scan Combinations and Permutations in a Linear Quadrupole Ion Trap.

PubMed

Snyder, Dalton T; Szalwinski, Lucas J; Cooks, R Graham

2017-10-17

Methods of performing precursor ion scans as well as neutral loss scans in a single linear quadrupole ion trap have recently been described. In this paper we report methodology for performing permutations of MS/MS scan modes, that is, ordered combinations of precursor, product, and neutral loss scans following a single ion injection event. Only particular permutations are allowed; the sequences demonstrated here are (1) multiple precursor ion scans, (2) precursor ion scans followed by a single neutral loss scan, (3) precursor ion scans followed by product ion scans, and (4) segmented neutral loss scans. (5) The common product ion scan can be performed earlier in these sequences, under certain conditions. Simultaneous scans can also be performed. These include multiple precursor ion scans, precursor ion scans with an accompanying neutral loss scan, and multiple neutral loss scans. We argue that the new capability to perform complex simultaneous and sequential MS n operations on single ion populations represents a significant step in increasing the selectivity of mass spectrometry.

Permutation coding technique for image recognition systems.

PubMed

Kussul, Ernst M; Baidyk, Tatiana N; Wunsch, Donald C; Makeyev, Oleksandr; Martín, Anabel

2006-11-01

A feature extractor and neural classifier for image recognition systems are proposed. The proposed feature extractor is based on the concept of random local descriptors (RLDs). It is followed by the encoder that is based on the permutation coding technique that allows to take into account not only detected features but also the position of each feature on the image and to make the recognition process invariant to small displacements. The combination of RLDs and permutation coding permits us to obtain a sufficiently general description of the image to be recognized. The code generated by the encoder is used as an input data for the neural classifier. Different types of images were used to test the proposed image recognition system. It was tested in the handwritten digit recognition problem, the face recognition problem, and the microobject shape recognition problem. The results of testing are very promising. The error rate for the Modified National Institute of Standards and Technology (MNIST) database is 0.44% and for the Olivetti Research Laboratory (ORL) database it is 0.1%.

A permutationally invariant full-dimensional ab initio potential energy surface for the abstraction and exchange channels of the H + CH{sub 4} system

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Jun, E-mail: jli15@cqu.edu.cn, E-mail: zhangdh@dicp.ac.cn; Department of Chemistry and Chemical Biology, University of New Mexico, Albuquerque, New Mexico 87131; Chen, Jun

2015-05-28

We report a permutationally invariant global potential energy surface (PES) for the H + CH{sub 4} system based on ∼63 000 data points calculated at a high ab initio level (UCCSD(T)-F12a/AVTZ) using the recently proposed permutation invariant polynomial-neural network method. The small fitting error (5.1 meV) indicates a faithful representation of the ab initio points over a large configuration space. The rate coefficients calculated on the PES using tunneling corrected transition-state theory and quasi-classical trajectory are found to agree well with the available experimental and previous quantum dynamical results. The calculated total reaction probabilities (J{sub tot} = 0) including themore » abstraction and exchange channels using the new potential by a reduced dimensional quantum dynamic method are essentially the same as those on the Xu-Chen-Zhang PES [Chin. J. Chem. Phys. 27, 373 (2014)].« less

Rank-based permutation approaches for non-parametric factorial designs.

PubMed

Umlauft, Maria; Konietschke, Frank; Pauly, Markus

2017-11-01

Inference methods for null hypotheses formulated in terms of distribution functions in general non-parametric factorial designs are studied. The methods can be applied to continuous, ordinal or even ordered categorical data in a unified way, and are based only on ranks. In this set-up Wald-type statistics and ANOVA-type statistics are the current state of the art. The first method is asymptotically exact but a rather liberal statistical testing procedure for small to moderate sample size, while the latter is only an approximation which does not possess the correct asymptotic α level under the null. To bridge these gaps, a novel permutation approach is proposed which can be seen as a flexible generalization of the Kruskal-Wallis test to all kinds of factorial designs with independent observations. It is proven that the permutation principle is asymptotically correct while keeping its finite exactness property when data are exchangeable. The results of extensive simulation studies foster these theoretical findings. A real data set exemplifies its applicability. © 2017 The British Psychological Society.

Structure-based Design of Cyclically Permuted HIV-1 gp120 Trimers That Elicit Neutralizing Antibodies*

PubMed Central

Kesavardhana, Sannula; Das, Raksha; Citron, Michael; Datta, Rohini; Ecto, Linda; Srilatha, Nonavinakere Seetharam; DiStefano, Daniel; Swoyer, Ryan; Joyce, Joseph G.; Dutta, Somnath; LaBranche, Celia C.; Montefiori, David C.; Flynn, Jessica A.; Varadarajan, Raghavan

2017-01-01

A major goal for HIV-1 vaccine development is an ability to elicit strong and durable broadly neutralizing antibody (bNAb) responses. The trimeric envelope glycoprotein (Env) spikes on HIV-1 are known to contain multiple epitopes that are susceptible to bNAbs isolated from infected individuals. Nonetheless, all trimeric and monomeric Env immunogens designed to date have failed to elicit such antibodies. We report the structure-guided design of HIV-1 cyclically permuted gp120 that forms homogeneous, stable trimers, and displays enhanced binding to multiple bNAbs, including VRC01, VRC03, VRC-PG04, PGT128, and the quaternary epitope-specific bNAbs PGT145 and PGDM1400. Constructs that were cyclically permuted in the V1 loop region and contained an N-terminal trimerization domain to stabilize V1V2-mediated quaternary interactions, showed the highest homogeneity and the best antigenic characteristics. In guinea pigs, a DNA prime-protein boost regimen with these new gp120 trimer immunogens elicited potent neutralizing antibody responses against highly sensitive Tier 1A isolates and weaker neutralizing antibody responses with an average titer of about 115 against a panel of heterologous Tier 2 isolates. A modest fraction of the Tier 2 virus neutralizing activity appeared to target the CD4 binding site on gp120. These results suggest that cyclically permuted HIV-1 gp120 trimers represent a viable platform in which further modifications may be made to eventually achieve protective bNAb responses. PMID:27879316

Development of estrogen receptor beta binding prediction model using large sets of chemicals.

PubMed

Sakkiah, Sugunadevi; Selvaraj, Chandrabose; Gong, Ping; Zhang, Chaoyang; Tong, Weida; Hong, Huixiao

2017-11-03

We developed an ER β binding prediction model to facilitate identification of chemicals specifically bind ER β or ER α together with our previously developed ER α binding model. Decision Forest was used to train ER β binding prediction model based on a large set of compounds obtained from EADB. Model performance was estimated through 1000 iterations of 5-fold cross validations. Prediction confidence was analyzed using predictions from the cross validations. Informative chemical features for ER β binding were identified through analysis of the frequency data of chemical descriptors used in the models in the 5-fold cross validations. 1000 permutations were conducted to assess the chance correlation. The average accuracy of 5-fold cross validations was 93.14% with a standard deviation of 0.64%. Prediction confidence analysis indicated that the higher the prediction confidence the more accurate the predictions. Permutation testing results revealed that the prediction model is unlikely generated by chance. Eighteen informative descriptors were identified to be important to ER β binding prediction. Application of the prediction model to the data from ToxCast project yielded very high sensitivity of 90-92%. Our results demonstrated ER β binding of chemicals could be accurately predicted using the developed model. Coupling with our previously developed ER α prediction model, this model could be expected to facilitate drug development through identification of chemicals that specifically bind ER β or ER α .

Ratio of n-3/n-6 PUFAs and risk of breast cancer: a meta-analysis of 274135 adult females from 11 independent prospective studies

PubMed Central

2014-01-01

Background Increased ratio of n-3/n-6 polyunsaturated fatty acids (PUFAs) in diet or serum may have a protective effect on the risk of breast cancer (BC); however, the conclusions from prospective studies are still controversial. The purpose of this study is to ascertain the relationship between intake ratio of n-3/n-6 PUFAs and the risk of BC, and estimate the potential summarized dose–response trend. Methods Relevant English-language studies were identified through Cochrane Library, PubMed and EMBASE database till April 2013. Eligible prospective studies reporting the multivariate adjusted risk ratios (RRs) for association of n-3/n-6 PUFAs ratio in diet or serum with BC risk. Data extraction was conducted independently by 2 investigators; disagreements were reconciled by consensus. Study quality was assessed using the Newcastle-Ottawa scale. Study-specific RRs were combined via a random-effects model. Results Six prospective nested case–control and 5 cohort studies, involving 8,331 BC events from 274,135 adult females across different countries, were included in present study. Subjects with higher dietary intake ratio of n-3/n-6 PUFAs have a significantly lower risk of BC among study populations (pooled RR = 0.90; 95% CI: 0.82, 0.99), and per 1/10 increment of ratio in diet was associated with a 6% reduction of BC risk (pooled RR = 0.94; 95% CI: 0.90, 0.99; P for linear trend = 0.012). USA subjects with higher ratio of n-3/n-6 in serum phospholipids (PL) have a significantly lower risk of BC (pooled RR = 0.62; 95% CI: 0.39, 0.97; I2 = 0.00%; P for metaregression = 0.103; P for a permutation test = 0.100), and per 1/10 increment of ratio in serum PL was associated with 27% reduction of BC risk (pooled RR = 0.73; 95% CI: 0.59, 0.91; P for linear trend = 0.004; P for metaregression = 0.082; P for a permutation test = 0.116). Conclusions Higher intake ratio of n-3/n-6 PUFAs is associated with lower risk of BC among females, which implies an important evidence for BC prevention and treatment is by increasing dietary intake ratio of n-3/n-6 PUFA. No firm conclusions from USA populations could be obtained, due to the limited numbers of USA studies. PMID:24548731

Two-level optimization of composite wing structures based on panel genetic optimization

NASA Astrophysics Data System (ADS)

Liu, Boyang

The design of complex composite structures used in aerospace or automotive vehicles presents a major challenge in terms of computational cost. Discrete choices for ply thicknesses and ply angles leads to a combinatorial optimization problem that is too expensive to solve with presently available computational resources. We developed the following methodology for handling this problem for wing structural design: we used a two-level optimization approach with response-surface approximations to optimize panel failure loads for the upper-level wing optimization. We tailored efficient permutation genetic algorithms to the panel stacking sequence design on the lower level. We also developed approach for improving continuity of ply stacking sequences among adjacent panels. The decomposition approach led to a lower-level optimization of stacking sequence with a given number of plies in each orientation. An efficient permutation genetic algorithm (GA) was developed for handling this problem. We demonstrated through examples that the permutation GAs are more efficient for stacking sequence optimization than a standard GA. Repair strategies for standard GA and the permutation GAs for dealing with constraints were also developed. The repair strategies can significantly reduce computation costs for both standard GA and permutation GA. A two-level optimization procedure for composite wing design subject to strength and buckling constraints is presented. At wing-level design, continuous optimization of ply thicknesses with orientations of 0°, 90°, and +/-45° is performed to minimize weight. At the panel level, the number of plies of each orientation (rounded to integers) and inplane loads are specified, and a permutation genetic algorithm is used to optimize the stacking sequence. The process begins with many panel genetic optimizations for a range of loads and numbers of plies of each orientation. Next, a cubic polynomial response surface is fitted to the optimum buckling load. The resulting response surface is used for wing-level optimization. In general, complex composite structures consist of several laminates. A common problem in the design of such structures is that some plies in the adjacent laminates terminate in the boundary between the laminates. These discontinuities may cause stress concentrations and may increase manufacturing difficulty and cost. We developed measures of continuity of two adjacent laminates. We studied tradeoffs between weight and continuity through a simple composite wing design. Finally, we compared the two-level optimization to a single-level optimization based on flexural lamination parameters. The single-level optimization is efficient and feasible for a wing consisting of unstiffened panels.

Graph Theory Meets Ab Initio Molecular Dynamics: Atomic Structures and Transformations at the Nanoscale

NASA Astrophysics Data System (ADS)

Pietrucci, Fabio; Andreoni, Wanda

2011-08-01

Social permutation invariant coordinates are introduced describing the bond network around a given atom. They originate from the largest eigenvalue and the corresponding eigenvector of the contact matrix, are invariant under permutation of identical atoms, and bear a clear signature of an order-disorder transition. Once combined with ab initio metadynamics, these coordinates are shown to be a powerful tool for the discovery of low-energy isomers of molecules and nanoclusters as well as for a blind exploration of isomerization, association, and dissociation reactions.

Finding fixed satellite service orbital allotments with a k-permutation algorithm

NASA Technical Reports Server (NTRS)

Reilly, Charles H.; Mount-Campbell, Clark A.; Gonsalvez, David J. A.

1990-01-01

A satellite system synthesis problem, the satellite location problem (SLP), is addressed. In SLP, orbital locations (longitudes) are allotted to geostationary satellites in the fixed satellite service. A linear mixed-integer programming model is presented that views SLP as a combination of two problems: the problem of ordering the satellites and the problem of locating the satellites given some ordering. A special-purpose heuristic procedure, a k-permutation algorithm, has been developed to find solutions to SLPs. Solutions to small sample problems are presented and analyzed on the basis of calculated interferences.

Permutation approach, high frequency trading and variety of micro patterns in financial time series

NASA Astrophysics Data System (ADS)

Aghamohammadi, Cina; Ebrahimian, Mehran; Tahmooresi, Hamed

2014-11-01

Permutation approach is suggested as a method to investigate financial time series in micro scales. The method is used to see how high frequency trading in recent years has affected the micro patterns which may be seen in financial time series. Tick to tick exchange rates are considered as examples. It is seen that variety of patterns evolve through time; and that the scale over which the target markets have no dominant patterns, have decreased steadily over time with the emergence of higher frequency trading.

Magic informationally complete POVMs with permutations

NASA Astrophysics Data System (ADS)

Planat, Michel; Gedik, Zafer

2017-09-01

Eigenstates of permutation gates are either stabilizer states (for gates in the Pauli group) or magic states, thus allowing universal quantum computation (Planat, Rukhsan-Ul-Haq 2017 Adv. Math. Phys. 2017, 5287862 (doi:10.1155/2017/5287862)). We show in this paper that a subset of such magic states, when acting on the generalized Pauli group, define (asymmetric) informationally complete POVMs. Such informationally complete POVMs, investigated in dimensions 2-12, exhibit simple finite geometries in their projector products and, for dimensions 4 and 8 and 9, relate to two-qubit, three-qubit and two-qutrit contextuality.

Hot topic: 16S rRNA gene sequencing reveals the microbiome of the virgin and pregnant bovine uterus.

PubMed

Moore, S G; Ericsson, A C; Poock, S E; Melendez, P; Lucy, M C

2017-06-01

We tested the hypothesis that the uterus of virgin heifers and pregnant cows possessed a resident microbiome by 16S rRNA gene sequencing of the virgin and pregnant bovine uterus. The endometrium of 10 virgin heifers in estrus and the amniotic fluid, placentome, intercotyledonary placenta, cervical lumen, and external cervix surface (control) of 5 pregnant cows were sampled using aseptic techniques. The DNA was extracted, the V4 hypervariable region of the 16S rRNA gene was amplified, and amplicons were sequenced using Illumina MiSeq technology (Illumina Inc., San Diego, CA). Operational taxonomic units (OTU) were generated from the sequences using Qiime v1.8 software, and taxonomy was assigned using the Greengenes database. The effect of tissue on the microbial composition within the pregnant uterus was tested using univariate (mixed model) and multivariate (permutational multivariate ANOVA) procedures. Amplicons of 16S rRNA gene were generated in all samples, supporting the contention that the uterus of virgin heifers and pregnant cows contained a microbiome. On average, 53, 199, 380, 382, 525, and 13,589 reads annotated as 16, 35, 43, 63, 48, and 176 OTU in the placentome, virgin endometrium, amniotic fluid, cervical lumen, intercotyledonary placenta, and external surface of the cervix, respectively, were generated. The 3 most abundant phyla in the uterus of the virgin heifers and pregnant cows were Firmicutes, Bacteroidetes, and Proteobacteria, and they accounted for approximately 40, 35, and 10% of the sequences, respectively. Phyla abundance was similar between the tissues of the pregnant uterus. Principal component analysis, one-way PERMANOVA analysis of the Bray-Curtis similarity index, and mixed model analysis of the Shannon diversity index and Chao1 index demonstrated that the microbiome of the control tissue (external surface of the cervix) was significantly different from that of the amniotic fluid, intercotyledonary placenta, and placentome tissues. Interestingly, many bacterial species associated with postpartum uterine disease (i.e., Trueperella spp., Acinetobacter spp., Fusobacteria spp., Proteus spp., Prevotella spp., and Peptostreptococcus spp.) were also present in the uterus of virgin heifers and of pregnant cows. The presence of 16S rRNA gene sequence reads in the samples from the current study suggests that the uterine microbiome is established by the time a female reaches reproductive maturity, and that pregnancies are established and maintained in the presence of a uterine microbiome. Copyright © 2017 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Efficient identification of context dependent subgroups of risk from genome wide association studies

PubMed Central

Dyson, Greg; Sing, Charles F.

2014-01-01

We have developed a modified Patient Rule-Induction Method (PRIM) as an alternative strategy for analyzing representative samples of non-experimental human data to estimate and test the role of genomic variations as predictors of disease risk in etiologically heterogeneous sub-samples. A computational limit of the proposed strategy is encountered when the number of genomic variations (predictor variables) under study is large (> 500) because permutations are used to generate a null distribution to test the significance of a term (defined by values of particular variables) that characterizes a sub-sample of individuals through the peeling and pasting processes. As an alternative, in this paper we introduce a theoretical strategy that facilitates the quick calculation of Type I and Type II errors in the evaluation of terms in the peeling and pasting processes carried out in the execution of a PRIM analysis that are underestimated and non-existent, respectively, when a permutation-based hypothesis test is employed. The resultant savings in computational time makes possible the consideration of larger numbers of genomic variations (an example genome wide association study is given) in the selection of statistically significant terms in the formulation of PRIM prediction models. PMID:24570412

Analysis of Feature Intervisibility and Cumulative Visibility Using GIS, Bayesian and Spatial Statistics: A Study from the Mandara Mountains, Northern Cameroon

PubMed Central

Wright, David K.; MacEachern, Scott; Lee, Jaeyong

2014-01-01

The locations of diy-geδ-bay (DGB) sites in the Mandara Mountains, northern Cameroon are hypothesized to occur as a function of their ability to see and be seen from points on the surrounding landscape. A series of geostatistical, two-way and Bayesian logistic regression analyses were performed to test two hypotheses related to the intervisibility of the sites to one another and their visual prominence on the landscape. We determine that the intervisibility of the sites to one another is highly statistically significant when compared to 10 stratified-random permutations of DGB sites. Bayesian logistic regression additionally demonstrates that the visibility of the sites to points on the surrounding landscape is statistically significant. The location of sites appears to have also been selected on the basis of lower slope than random permutations of sites. Using statistical measures, many of which are not commonly employed in archaeological research, to evaluate aspects of visibility on the landscape, we conclude that the placement of DGB sites improved their conspicuousness for enhanced ritual, social cooperation and/or competition purposes. PMID:25383883

A Permutation-Randomization Approach to Test the Spatial Distribution of Plant Diseases.

PubMed

Lione, G; Gonthier, P

2016-01-01

The analysis of the spatial distribution of plant diseases requires the availability of trustworthy geostatistical methods. The mean distance tests (MDT) are here proposed as a series of permutation and randomization tests to assess the spatial distribution of plant diseases when the variable of phytopathological interest is categorical. A user-friendly software to perform the tests is provided. Estimates of power and type I error, obtained with Monte Carlo simulations, showed the reliability of the MDT (power > 0.80; type I error < 0.05). A biological validation on the spatial distribution of spores of two fungal pathogens causing root rot on conifers was successfully performed by verifying the consistency between the MDT responses and previously published data. An application of the MDT was carried out to analyze the relation between the plantation density and the distribution of the infection of Gnomoniopsis castanea, an emerging fungal pathogen causing nut rot on sweet chestnut. Trees carrying nuts infected by the pathogen were randomly distributed in areas with different plantation densities, suggesting that the distribution of G. castanea was not related to the plantation density. The MDT could be used to analyze the spatial distribution of plant diseases both in agricultural and natural ecosystems.

Folding pathway of a multidomain protein depends on its topology of domain connectivity

PubMed Central

Inanami, Takashi; Terada, Tomoki P.; Sasai, Masaki

2014-01-01

How do the folding mechanisms of multidomain proteins depend on protein topology? We addressed this question by developing an Ising-like structure-based model and applying it for the analysis of free-energy landscapes and folding kinetics of an example protein, Escherichia coli dihydrofolate reductase (DHFR). DHFR has two domains, one comprising discontinuous N- and C-terminal parts and the other comprising a continuous middle part of the chain. The simulated folding pathway of DHFR is a sequential process during which the continuous domain folds first, followed by the discontinuous domain, thereby avoiding the rapid decrease in conformation entropy caused by the association of the N- and C-terminal parts during the early phase of folding. Our simulated results consistently explain the observed experimental data on folding kinetics and predict an off-pathway structural fluctuation at equilibrium. For a circular permutant for which the topological complexity of wild-type DHFR is resolved, the balance between energy and entropy is modulated, resulting in the coexistence of the two folding pathways. This coexistence of pathways should account for the experimentally observed complex folding behavior of the circular permutant. PMID:25267632

Exposures Related to House Dust Microbiota in a U.S. Farming Population.

PubMed

Lee, Mi Kyeong; Carnes, Megan U; Butz, Natasha; Azcarate-Peril, M Andrea; Richards, Marie; Umbach, David M; Thorne, Peter S; Beane Freeman, Laura E; Peddada, Shyamal D; London, Stephanie J

2018-06-01

Environmental factors can influence the house dust microbiota, which may impact health outcomes. Little is known about how farming exposures impact the indoor microbiota. We aimed to identify exposures related to bacterial communities in house dust in a U.S. farming population. We used 16S rRNA amplicon sequencing to characterize bacterial communities in vacuumed dust samples from the bedrooms of a subset of 879 households of farmers and farmers' spouses enrolled in the Agricultural Lung Health Study (ALHS), a case-control study of asthma nested within the Agricultural Health Study (AHS) in North Carolina and Iowa. Information on current farming (past 12 mo), including both crop and animal farming, and other potential microbial sources was obtained via questionnaires. We used linear regression to evaluate associations between exposures and bacterial diversity within each sample, analysis of similarity (ANOSIM), and permutational multivariate analysis of variance (PERMANOVA) to identify exposures related to diversity between samples, and analysis of composition of microbiome to examine whether exposures related to diversity were also related to differential abundance of specific operational taxonomic units (OTUs). Current farming was positively associated with bacterial diversity in house dust, with or without adjustment for nonfarm exposures related to diversity, including presence of indoor pets, home condition, and season of dust collection. Many taxa exhibited differential abundance related to farming. Some taxa in the phyla Chloroflexi and Verrucomicrobia were associated [false discovery rate (FDR)<0.05] with farming but not with other nonfarm factors. Many taxa correlated with the concentration of house dust of endotoxin, commonly studied as a general marker of exposure to the farming environment. In this farming population, house dust microbiota differed by current farming status. Understanding the determinants of the indoor microbiota is the first step toward understanding potential relationships with health outcomes. https://doi.org/10.1289/EHP3145.

454 pyrosequencing analysis on faecal samples from a randomized DBPC trial of colicky infants treated with Lactobacillus reuteri DSM 17938.

PubMed

Roos, Stefan; Dicksved, Johan; Tarasco, Valentina; Locatelli, Emanuela; Ricceri, Fulvio; Grandin, Ulf; Savino, Francesco

2013-01-01

To analyze the global microbial composition, using large-scale DNA sequencing of 16 S rRNA genes, in faecal samples from colicky infants given L. reuteri DSM 17938 or placebo. Twenty-nine colicky infants (age 10-60 days) were enrolled and randomly assigned to receive either Lactobacillus reuteri (10(8) cfu) or a placebo once daily for 21 days. Responders were defined as subjects with a decrease of 50% in daily crying time at day 21 compared with the starting point. The microbiota of faecal samples from day 1 and 21 were analyzed using 454 pyrosequencing. The primers: Bakt_341F and Bakt_805R, complemented with 454 adapters and sample specific barcodes were used for PCR amplification of the 16 S rRNA genes. The structure of the data was explored by using permutational multivariate analysis of variance and effects of different variables were visualized with ordination analysis. The infants' faecal microbiota were composed of Proteobacteria, Firmicutes, Actinobacteria and Bacteroidetes as the four main phyla. The composition of the microbiota in infants with colic had very high inter-individual variability with Firmicutes/Bacteroidetes ratios varying from 4000 to 0.025. On an individual basis, the microbiota was, however, relatively stable over time. Treatment with L. reuteri DSM 17938 did not change the global composition of the microbiota, but when comparing responders with non-responders the group responders had an increased relative abundance of the phyla Bacteroidetes and genus Bacteroides at day 21 compared with day 0. Furthermore, the phyla composition of the infants at day 21 could be divided into three enterotype groups, dominated by Firmicutes, Bacteroidetes, and Actinobacteria, respectively. L. reuteri DSM 17938 did not affect the global composition of the microbiota. However, the increase of Bacteroidetes in the responder infants indicated that a decrease in colicky symptoms was linked to changes of the microbiota. ClinicalTrials.gov NCT00893711.

Nontargeted metabolomics approach for the differentiation of cultivation ages of mountain cultivated ginseng leaves using UHPLC/QTOF-MS.

PubMed

Chang, Xiangwei; Zhang, Juanjuan; Li, Dekun; Zhou, Dazheng; Zhang, Yuling; Wang, Jincheng; Hu, Bing; Ju, Aichun; Ye, Zhengliang

2017-07-15

The adulteration or falsification of the cultivation age of mountain cultivated ginseng (MCG) has been a serious problem in the commercial MCG market. To develop an efficient discrimination tool for the cultivation age and to explore potential age-dependent markers, an optimized ultra high-performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UHPLC/QTOF-MS)-based metabolomics approach was applied in the global metabolite profiling of 156 MCG leaf (MGL) samples aged from 6 to 18 years. Multivariate statistical methods such as principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to compare the derived patterns between MGL samples of different cultivation ages. The present study demonstrated that 6-18-year-old MGL samples can be successfully discriminated using two simple successive steps, together with four PLS-DA discrimination models. Furthermore, 39 robust age-dependent markers enabling differentiation among the 6-18-year-old MGL samples were discovered. The results were validated by a permutation test and an external test set to verify the predictability and reliability of the established discrimination models. More importantly, without destroying the MCG roots, the proposed approach could also be applied to discriminate MCG root ages indirectly, using a minimum amount of homophyletic MGL samples combined with the established four PLS-DA models and identified markers. Additionally, to the best of our knowledge, this is the first study in which 6-18-year-old MCG root ages have been nondestructively differentiated by analyzing homophyletic MGL samples using UHPLC/QTOF-MS analysis and two simple successive steps together with four PLS-DA models. The method developed in this study can be used as a standard protocol for discriminating and predicting MGL ages directly and homophyletic MCG root ages indirectly. Copyright © 2017 Elsevier B.V. All rights reserved.

Application of Mathematical Signal Processing Techniques to Mission Systems. (l’Application des techniques mathematiques du traitement du signal aux systemes de conduite des missions)

DTIC Science & Technology

1999-11-01

represents the linear time invariant (LTI) response of the combined analysis /synthesis system while the second repre- sents the aliasing introduced into...effectively to implement voice scrambling systems based on time - frequency permutation . The most general form of such a system is shown in Fig. 22 where...92201 NEUILLY-SUR-SEINE CEDEX, FRANCE RTO LECTURE SERIES 216 Application of Mathematical Signal Processing Techniques to Mission Systems (1

SCOPES: steganography with compression using permutation search

NASA Astrophysics Data System (ADS)

Boorboor, Sahar; Zolfaghari, Behrouz; Mozafari, Saadat Pour

2011-10-01

LSB (Least Significant Bit) is a widely used method for image steganography, which hides the secret message as a bit stream in LSBs of pixel bytes in the cover image. This paper proposes a variant of LSB named SCOPES that encodes and compresses the secret message while being hidden through storing addresses instead of message bytes. Reducing the length of the stored message improves the storage capacity and makes the stego image visually less suspicious to the third party. The main idea behind the SCOPES approach is dividing the message into 3-character segments, seeking each segment in the cover image and storing the address of the position containing the segment instead of the segment itself. In this approach, every permutation of the 3 bytes (if found) can be stored along with some extra bits indicating the permutation. In some rare cases the segment may not be found in the image and this can cause the message to be expanded by some overhead bits2 instead of being compressed. But experimental results show that SCOPES performs overlay better than traditional LSB even in the worst cases.

An effective hybrid immune algorithm for solving the distributed permutation flow-shop scheduling problem

NASA Astrophysics Data System (ADS)

Xu, Ye; Wang, Ling; Wang, Shengyao; Liu, Min

2014-09-01

In this article, an effective hybrid immune algorithm (HIA) is presented to solve the distributed permutation flow-shop scheduling problem (DPFSP). First, a decoding method is proposed to transfer a job permutation sequence to a feasible schedule considering both factory dispatching and job sequencing. Secondly, a local search with four search operators is presented based on the characteristics of the problem. Thirdly, a special crossover operator is designed for the DPFSP, and mutation and vaccination operators are also applied within the framework of the HIA to perform an immune search. The influence of parameter setting on the HIA is investigated based on the Taguchi method of design of experiment. Extensive numerical testing results based on 420 small-sized instances and 720 large-sized instances are provided. The effectiveness of the HIA is demonstrated by comparison with some existing heuristic algorithms and the variable neighbourhood descent methods. New best known solutions are obtained by the HIA for 17 out of 420 small-sized instances and 585 out of 720 large-sized instances.

Cluster mass inference via random field theory.

PubMed

Zhang, Hui; Nichols, Thomas E; Johnson, Timothy D

2009-01-01

Cluster extent and voxel intensity are two widely used statistics in neuroimaging inference. Cluster extent is sensitive to spatially extended signals while voxel intensity is better for intense but focal signals. In order to leverage strength from both statistics, several nonparametric permutation methods have been proposed to combine the two methods. Simulation studies have shown that of the different cluster permutation methods, the cluster mass statistic is generally the best. However, to date, there is no parametric cluster mass inference available. In this paper, we propose a cluster mass inference method based on random field theory (RFT). We develop this method for Gaussian images, evaluate it on Gaussian and Gaussianized t-statistic images and investigate its statistical properties via simulation studies and real data. Simulation results show that the method is valid under the null hypothesis and demonstrate that it can be more powerful than the cluster extent inference method. Further, analyses with a single subject and a group fMRI dataset demonstrate better power than traditional cluster size inference, and good accuracy relative to a gold-standard permutation test.

Bayesian inference on risk differences: an application to multivariate meta-analysis of adverse events in clinical trials.

PubMed

Chen, Yong; Luo, Sheng; Chu, Haitao; Wei, Peng

2013-05-01

Multivariate meta-analysis is useful in combining evidence from independent studies which involve several comparisons among groups based on a single outcome. For binary outcomes, the commonly used statistical models for multivariate meta-analysis are multivariate generalized linear mixed effects models which assume risks, after some transformation, follow a multivariate normal distribution with possible correlations. In this article, we consider an alternative model for multivariate meta-analysis where the risks are modeled by the multivariate beta distribution proposed by Sarmanov (1966). This model have several attractive features compared to the conventional multivariate generalized linear mixed effects models, including simplicity of likelihood function, no need to specify a link function, and has a closed-form expression of distribution functions for study-specific risk differences. We investigate the finite sample performance of this model by simulation studies and illustrate its use with an application to multivariate meta-analysis of adverse events of tricyclic antidepressants treatment in clinical trials.

Sample classification for improved performance of PLS models applied to the quality control of deep-frying oils of different botanic origins analyzed using ATR-FTIR spectroscopy.

PubMed

Kuligowski, Julia; Carrión, David; Quintás, Guillermo; Garrigues, Salvador; de la Guardia, Miguel

2011-01-01

The selection of an appropriate calibration set is a critical step in multivariate method development. In this work, the effect of using different calibration sets, based on a previous classification of unknown samples, on the partial least squares (PLS) regression model performance has been discussed. As an example, attenuated total reflection (ATR) mid-infrared spectra of deep-fried vegetable oil samples from three botanical origins (olive, sunflower, and corn oil), with increasing polymerized triacylglyceride (PTG) content induced by a deep-frying process were employed. The use of a one-class-classifier partial least squares-discriminant analysis (PLS-DA) and a rooted binary directed acyclic graph tree provided accurate oil classification. Oil samples fried without foodstuff could be classified correctly, independent of their PTG content. However, class separation of oil samples fried with foodstuff, was less evident. The combined use of double-cross model validation with permutation testing was used to validate the obtained PLS-DA classification models, confirming the results. To discuss the usefulness of the selection of an appropriate PLS calibration set, the PTG content was determined by calculating a PLS model based on the previously selected classes. In comparison to a PLS model calculated using a pooled calibration set containing samples from all classes, the root mean square error of prediction could be improved significantly using PLS models based on the selected calibration sets using PLS-DA, ranging between 1.06 and 2.91% (w/w).

Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA

PubMed Central

Kelly, Brendan J.; Gross, Robert; Bittinger, Kyle; Sherrill-Mix, Scott; Lewis, James D.; Collman, Ronald G.; Bushman, Frederic D.; Li, Hongzhe

2015-01-01

Motivation: The variation in community composition between microbiome samples, termed beta diversity, can be measured by pairwise distance based on either presence–absence or quantitative species abundance data. PERMANOVA, a permutation-based extension of multivariate analysis of variance to a matrix of pairwise distances, partitions within-group and between-group distances to permit assessment of the effect of an exposure or intervention (grouping factor) upon the sampled microbiome. Within-group distance and exposure/intervention effect size must be accurately modeled to estimate statistical power for a microbiome study that will be analyzed with pairwise distances and PERMANOVA. Results: We present a framework for PERMANOVA power estimation tailored to marker-gene microbiome studies that will be analyzed by pairwise distances, which includes: (i) a novel method for distance matrix simulation that permits modeling of within-group pairwise distances according to pre-specified population parameters; (ii) a method to incorporate effects of different sizes within the simulated distance matrix; (iii) a simulation-based method for estimating PERMANOVA power from simulated distance matrices; and (iv) an R statistical software package that implements the above. Matrices of pairwise distances can be efficiently simulated to satisfy the triangle inequality and incorporate group-level effects, which are quantified by the adjusted coefficient of determination, omega-squared (ω2). From simulated distance matrices, available PERMANOVA power or necessary sample size can be estimated for a planned microbiome study. Availability and implementation: http://github.com/brendankelly/micropower. Contact: brendank@mail.med.upenn.edu or hongzhe@upenn.edu PMID:25819674

The microbiome of otitis media with effusion.

PubMed

Chan, Chun Ling; Wabnitz, David; Bardy, Jake Jervis; Bassiouni, Ahmed; Wormald, Peter-John; Vreugde, Sarah; Psaltis, Alkis James

2016-12-01

The adenoid pad has been considered a reservoir for bacteria in the pathogenesis of otitis media with effusion. This study aimed to characterize the middle ear microbiota in children with otitis media with effusion and establish whether a correlation exists between the middle ear and adenoid microbiota. Prospective, controlled study. Middle ear aspirates adenoid pad swabs were collected from 23 children undergoing ventilation tube insertion. Adenoid swabs from patients without ear disease were controls. Samples were analyzed using 16S rRNA sequencing on the Illumina MiSeq platform. Thirty-five middle ear samples were collected. The middle ear effusion microbiota was dominated by Alloiococcus otitidis (23% mean relative abundance), Haemophilus (22%), Moraxella (5%), and Streptococcus (5%). Alloiococcus shared an inverse correlation with Haemophilus (P = .049) and was found in greater relative abundance in unilateral effusion (P = .004). The microbiota of bilateral effusions from the same patient were similar (P < .001). However, the otitis media with effusion microbiota were found to be dissimilar to that of the adenoid (P = .01), whereas the adenoid microbiota of otitis media with effusion and control patients were similar (P > .05) (permutational multivariate analysis of the variance). Dissimilarities between the local microbiota of the adenoid and the middle ear question the theory that the adenoid pad is a significant reservoir to the middle ear in children with otitis media with effusion. A otitidis had the greatest cumulative relative abundance, particularly in unilateral effusions, and shares an inverse correlation with the relative abundance of Haemophilus. NA Laryngoscope, 126:2844-2851, 2016. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables.

PubMed

Pounds, Stan; Cheng, Cheng; Cao, Xueyuan; Crews, Kristine R; Plunkett, William; Gandhi, Varsha; Rubnitz, Jeffrey; Ribeiro, Raul C; Downing, James R; Lamba, Jatinder

2009-08-15

In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables. Projection onto the most interesting statistical evidence (PROMISE) is proposed as a general procedure to identify genomic variables that exhibit a specific biologically interesting pattern of association with multiple endpoint variables. Biological knowledge of the endpoint variables is used to define a vector that represents the biologically most interesting values for statistics that characterize the associations of the endpoint variables with a genomic variable. A test statistic is defined as the dot-product of the vector of the observed association statistics and the vector of the most interesting values of the association statistics. By definition, this test statistic is proportional to the length of the projection of the observed vector of correlations onto the vector of most interesting associations. Statistical significance is determined via permutation. In simulation studies and an example application, PROMISE shows greater statistical power to identify genes with the interesting pattern of associations than classical multivariate procedures, individual endpoint analyses or listing genes that have the pattern of interest and are significant in more than one individual endpoint analysis. Documented R routines are freely available from www.stjuderesearch.org/depts/biostats and will soon be available as a Bioconductor package from www.bioconductor.org.

A k-permutation algorithm for Fixed Satellite Service orbital allotments

NASA Technical Reports Server (NTRS)

Reilly, Charles H.; Mount-Campbell, Clark A.; Gonsalvez, David J. A.

1988-01-01

A satellite system synthesis problem, the satellite location problem (SLP), is addressed in this paper. In SLP, orbital locations (longitudes) are allotted to geostationary satellites in the Fixed Satellite Service. A linear mixed-integer programming model is presented that views SLP as a combination of two problems: (1) the problem of ordering the satellites and (2) the problem of locating the satellites given some ordering. A special-purpose heuristic procedure, a k-permutation algorithm, that has been developed to find solutions to SLPs formulated in the manner suggested is described. Solutions to small example problems are presented and analyzed.

Convergence to equilibrium under a random Hamiltonian.

PubMed

Brandão, Fernando G S L; Ćwikliński, Piotr; Horodecki, Michał; Horodecki, Paweł; Korbicz, Jarosław K; Mozrzymas, Marek

2012-09-01

We analyze equilibration times of subsystems of a larger system under a random total Hamiltonian, in which the basis of the Hamiltonian is drawn from the Haar measure. We obtain that the time of equilibration is of the order of the inverse of the arithmetic average of the Bohr frequencies. To compute the average over a random basis, we compute the inverse of a matrix of overlaps of operators which permute four systems. We first obtain results on such a matrix for a representation of an arbitrary finite group and then apply it to the particular representation of the permutation group under consideration.

Convergence to equilibrium under a random Hamiltonian

NASA Astrophysics Data System (ADS)

Brandão, Fernando G. S. L.; Ćwikliński, Piotr; Horodecki, Michał; Horodecki, Paweł; Korbicz, Jarosław K.; Mozrzymas, Marek

2012-09-01

We analyze equilibration times of subsystems of a larger system under a random total Hamiltonian, in which the basis of the Hamiltonian is drawn from the Haar measure. We obtain that the time of equilibration is of the order of the inverse of the arithmetic average of the Bohr frequencies. To compute the average over a random basis, we compute the inverse of a matrix of overlaps of operators which permute four systems. We first obtain results on such a matrix for a representation of an arbitrary finite group and then apply it to the particular representation of the permutation group under consideration.

A new Nawaz-Enscore-Ham-based heuristic for permutation flow-shop problems with bicriteria of makespan and machine idle time

NASA Astrophysics Data System (ADS)

Liu, Weibo; Jin, Yan; Price, Mark

2016-10-01

A new heuristic based on the Nawaz-Enscore-Ham algorithm is proposed in this article for solving a permutation flow-shop scheduling problem. A new priority rule is proposed by accounting for the average, mean absolute deviation, skewness and kurtosis, in order to fully describe the distribution style of processing times. A new tie-breaking rule is also introduced for achieving effective job insertion with the objective of minimizing both makespan and machine idle time. Statistical tests illustrate better solution quality of the proposed algorithm compared to existing benchmark heuristics.

Neighbourhood generation mechanism applied in simulated annealing to job shop scheduling problems

NASA Astrophysics Data System (ADS)

Cruz-Chávez, Marco Antonio

2015-11-01

This paper presents a neighbourhood generation mechanism for the job shop scheduling problems (JSSPs). In order to obtain a feasible neighbour with the generation mechanism, it is only necessary to generate a permutation of an adjacent pair of operations in a scheduling of the JSSP. If there is no slack time between the adjacent pair of operations that is permuted, then it is proven, through theory and experimentation, that the new neighbour (schedule) generated is feasible. It is demonstrated that the neighbourhood generation mechanism is very efficient and effective in a simulated annealing.

Analysis of endomorphisms

NASA Astrophysics Data System (ADS)

Conti, Roberto; Hong, Jeong Hee; Szymański, Wojciech

2012-02-01

In this expository article, we discuss the recent progress in the study of endomorphisms and automorphisms of the Cuntz algebras and, more generally graph C* -algebras (or Cuntz-Krieger algebras). In particular, we discuss the definition and properties of both the full and the restricted Weyl group of such an algebra. Then we outline a powerful combinatorial approach to analysis of endomorphisms arising from permutation unitaries. The restricted Weyl group consists of automorphisms of this type. We also discuss the action of the restricted Weyl group on the diagonal MASA and its relationship with the automorphism group of the full two-sided n-shift. Finally, several open problems are presented.

Rotational excitations of N2O in small helium clusters and the role of Bose permutation symmetry

NASA Astrophysics Data System (ADS)

Paesani, F.; Whaley, K. B.

2004-09-01

We present a detailed study of the energetics, structures, and Bose properties of small clusters of 4He containing a single nitrous oxide (N2O) molecule, from N=1 4He up to sizes corresponding to completion of the first solvation shell around N2O (N=16 4He). Ground state properties are calculated using the importance-sampled rigid-body diffusion Monte Carlo method, rotational excited state calculations are made with the projection operator imaginary time spectral evolution method, and Bose permutation exchange and associated superfluid properties are calculated with the finite temperature path integral method. For N⩽5 the helium atoms are seen to form an equatorial ring around the molecular axis, at N=6 helium density starts to occupy the second (local) minimum of the N2O-He interaction at the oxygen side of the molecule, and N=9 is the critical size at which there is onset of helium solvation all along the molecular axis. For N⩾8 six 4He atoms are distributed in a symmetric, quasirigid ring around N2O. Path integral calculations show essentially complete superfluid response to rotation about the molecular axis for N⩾5, and a rise of the perpendicular superfluid response from zero to appreciable values for N⩾8. Rotational excited states are computed for three values of the total angular momentum, J=1-3, and the energy levels fitted to obtain effective spectroscopic constants that show excellent agreement with the experimentally observed N dependence of the effective rotational constant Beff. The non-monotonic behavior of the rotational constant is seen to be due to the onset of long 4He permutation exchanges and associated perpendicular superfluid response of the clusters for N⩾8. We provide a detailed analysis of the role of the helium solvation structure and superfluid properties in determining the effective rotational constants.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daugherty, Ashley B.; Horton, John R.; Cheng, Xiaodong

Circular permutation of the NADPH-dependent oxidoreductase Old Yellow Enzyme from Saccharomyces pastorianus (OYE1) can significantly enhance the enzyme’s catalytic performance. Termini relocation into four regions of the protein (sectors I–IV) near the active site has proven effective in altering enzyme function. To better understand the structural consequences and rationalize the observed functional gains in these OYE1 variants, we selected representatives from sectors I–III for further characterization by biophysical methods and X-ray crystallography. These investigations not only show trends in enzyme stability and quaternary structure as a function of termini location but also provide a possible explanation for the catalytic gainsmore » in our top-performing OYE variant (new N-terminus at residue 303; sector III). Crystallographic analysis indicates that termini relocation into sector III affects the loop β6 region (amino acid positions: 290–310) of OYE1, which forms a lid over the active site. Peptide backbone cleavage greatly enhances local flexibility, effectively converting the loop into a tether and consequently increasing the environmental exposure of the active site. Interestingly, such an active site remodeling does not negatively impact the enzyme’s activity and stereoselectivity; neither does it perturb the conformation of other key active site residues with the exception of Y375. These observations were confirmed in truncation experiments, deleting all residues of the loop β6 region in our OYE variant. Intrigued by the finding that circular permutation leaves most of the key catalytic residues unchanged, we also tested OYE permutants for possible additive or synergistic effects of amino acid substitutions. Distinct functional changes in these OYE variants were detected upon mutations at W116, known in native OYE1 to cause inversion of diastereoselectivity for (S)-carvone reduction. In conclusion, our findings demonstrate the contribution of loop β6 toward determining the stereoselectivity of OYE1, an important insight for future OYE engineering efforts.« less

Comparing vector-based and Bayesian memory models using large-scale datasets: User-generated hashtag and tag prediction on Twitter and Stack Overflow.

PubMed

Stanley, Clayton; Byrne, Michael D

2016-12-01

The growth of social media and user-created content on online sites provides unique opportunities to study models of human declarative memory. By framing the task of choosing a hashtag for a tweet and tagging a post on Stack Overflow as a declarative memory retrieval problem, 2 cognitively plausible declarative memory models were applied to millions of posts and tweets and evaluated on how accurately they predict a user's chosen tags. An ACT-R based Bayesian model and a random permutation vector-based model were tested on the large data sets. The results show that past user behavior of tag use is a strong predictor of future behavior. Furthermore, past behavior was successfully incorporated into the random permutation model that previously used only context. Also, ACT-R's attentional weight term was linked to an entropy-weighting natural language processing method used to attenuate high-frequency words (e.g., articles and prepositions). Word order was not found to be a strong predictor of tag use, and the random permutation model performed comparably to the Bayesian model without including word order. This shows that the strength of the random permutation model is not in the ability to represent word order, but rather in the way in which context information is successfully compressed. The results of the large-scale exploration show how the architecture of the 2 memory models can be modified to significantly improve accuracy, and may suggest task-independent general modifications that can help improve model fit to human data in a much wider range of domains. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Visualization of Global Disease Burden for the Optimization of Patient Management and Treatment.

PubMed

Schlee, Winfried; Hall, Deborah A; Edvall, Niklas K; Langguth, Berthold; Canlon, Barbara; Cederroth, Christopher R

2017-01-01

The assessment and treatment of complex disorders is challenged by the multiple domains and instruments used to evaluate clinical outcome. With the large number of assessment tools typically used in complex disorders comes the challenge of obtaining an integrative view of disease status to further evaluate treatment outcome both at the individual level and at the group level. Radar plots appear as an attractive visual tool to display multivariate data on a two-dimensional graphical illustration. Here, we describe the use of radar plots for the visualization of disease characteristics applied in the context of tinnitus, a complex and heterogeneous condition, the treatment of which has shown mixed success. Data from two different cohorts, the Swedish Tinnitus Outreach Project (STOP) and the Tinnitus Research Initiative (TRI) database, were used. STOP is a population-based cohort where cross-sectional data from 1,223 non-tinnitus and 933 tinnitus subjects were analyzed. By contrast, the TRI contained data from 571 patients who underwent various treatments and whose Clinical Global Impression (CGI) score was accessible to infer treatment outcome. In the latter, 34,560 permutations were tested to evaluate whether a particular ordering of the instruments could reflect better the treatment outcome measured with the CGI. Radar plots confirmed that tinnitus subtypes such as occasional and chronic tinnitus from the STOP cohort could be strikingly different, and helped appreciate a gender bias in tinnitus severity. Radar plots with greater surface areas were consistent with greater burden, and enabled a rapid appreciation of the global distress associated with tinnitus in patients categorized according to tinnitus severity. Permutations in the arrangement of instruments allowed to identify a configuration with minimal variance and maximized surface difference between CGI groups from the TRI database, thus affording a means of optimally evaluating the outcomes in individual patients. We anticipate such a tool to become a starting point for more sophisticated measures in clinical outcomes, applicable not only in the context of tinnitus but also in other complex diseases where the integration of multiple variables is needed for a comprehensive evaluation of treatment response.

Multivariate analysis in thoracic research.

PubMed

Mengual-Macenlle, Noemí; Marcos, Pedro J; Golpe, Rafael; González-Rivas, Diego

2015-03-01

Multivariate analysis is based in observation and analysis of more than one statistical outcome variable at a time. In design and analysis, the technique is used to perform trade studies across multiple dimensions while taking into account the effects of all variables on the responses of interest. The development of multivariate methods emerged to analyze large databases and increasingly complex data. Since the best way to represent the knowledge of reality is the modeling, we should use multivariate statistical methods. Multivariate methods are designed to simultaneously analyze data sets, i.e., the analysis of different variables for each person or object studied. Keep in mind at all times that all variables must be treated accurately reflect the reality of the problem addressed. There are different types of multivariate analysis and each one should be employed according to the type of variables to analyze: dependent, interdependence and structural methods. In conclusion, multivariate methods are ideal for the analysis of large data sets and to find the cause and effect relationships between variables; there is a wide range of analysis types that we can use.

Improved diagonal queue medical image steganography using Chaos theory, LFSR, and Rabin cryptosystem.

PubMed

Jain, Mamta; Kumar, Anil; Choudhary, Rishabh Charan

2017-06-01

In this article, we have proposed an improved diagonal queue medical image steganography for patient secret medical data transmission using chaotic standard map, linear feedback shift register, and Rabin cryptosystem, for improvement of previous technique (Jain and Lenka in Springer Brain Inform 3:39-51, 2016). The proposed algorithm comprises four stages, generation of pseudo-random sequences (pseudo-random sequences are generated by linear feedback shift register and standard chaotic map), permutation and XORing using pseudo-random sequences, encryption using Rabin cryptosystem, and steganography using the improved diagonal queues. Security analysis has been carried out. Performance analysis is observed using MSE, PSNR, maximum embedding capacity, as well as by histogram analysis between various Brain disease stego and cover images.

Correlative and multivariate analysis of increased radon concentration in underground laboratory.

PubMed

Maletić, Dimitrije M; Udovičić, Vladimir I; Banjanac, Radomir M; Joković, Dejan R; Dragić, Aleksandar L; Veselinović, Nikola B; Filipović, Jelena

2014-11-01

The results of analysis using correlative and multivariate methods, as developed for data analysis in high-energy physics and implemented in the Toolkit for Multivariate Analysis software package, of the relations of the variation of increased radon concentration with climate variables in shallow underground laboratory is presented. Multivariate regression analysis identified a number of multivariate methods which can give a good evaluation of increased radon concentrations based on climate variables. The use of the multivariate regression methods will enable the investigation of the relations of specific climate variable with increased radon concentrations by analysis of regression methods resulting in 'mapped' underlying functional behaviour of radon concentrations depending on a wide spectrum of climate variables. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Multivariate Methods for Meta-Analysis of Genetic Association Studies.

PubMed

Dimou, Niki L; Pantavou, Katerina G; Braliou, Georgia G; Bagos, Pantelis G

2018-01-01

Multivariate meta-analysis of genetic association studies and genome-wide association studies has received a remarkable attention as it improves the precision of the analysis. Here, we review, summarize and present in a unified framework methods for multivariate meta-analysis of genetic association studies and genome-wide association studies. Starting with the statistical methods used for robust analysis and genetic model selection, we present in brief univariate methods for meta-analysis and we then scrutinize multivariate methodologies. Multivariate models of meta-analysis for a single gene-disease association studies, including models for haplotype association studies, multiple linked polymorphisms and multiple outcomes are discussed. The popular Mendelian randomization approach and special cases of meta-analysis addressing issues such as the assumption of the mode of inheritance, deviation from Hardy-Weinberg Equilibrium and gene-environment interactions are also presented. All available methods are enriched with practical applications and methodologies that could be developed in the future are discussed. Links for all available software implementing multivariate meta-analysis methods are also provided.

Analysis of small sample size studies using nonparametric bootstrap test with pooled resampling method.

PubMed

Dwivedi, Alok Kumar; Mallawaarachchi, Indika; Alvarado, Luis A

2017-06-30

Experimental studies in biomedical research frequently pose analytical problems related to small sample size. In such studies, there are conflicting findings regarding the choice of parametric and nonparametric analysis, especially with non-normal data. In such instances, some methodologists questioned the validity of parametric tests and suggested nonparametric tests. In contrast, other methodologists found nonparametric tests to be too conservative and less powerful and thus preferred using parametric tests. Some researchers have recommended using a bootstrap test; however, this method also has small sample size limitation. We used a pooled method in nonparametric bootstrap test that may overcome the problem related with small samples in hypothesis testing. The present study compared nonparametric bootstrap test with pooled resampling method corresponding to parametric, nonparametric, and permutation tests through extensive simulations under various conditions and using real data examples. The nonparametric pooled bootstrap t-test provided equal or greater power for comparing two means as compared with unpaired t-test, Welch t-test, Wilcoxon rank sum test, and permutation test while maintaining type I error probability for any conditions except for Cauchy and extreme variable lognormal distributions. In such cases, we suggest using an exact Wilcoxon rank sum test. Nonparametric bootstrap paired t-test also provided better performance than other alternatives. Nonparametric bootstrap test provided benefit over exact Kruskal-Wallis test. We suggest using nonparametric bootstrap test with pooled resampling method for comparing paired or unpaired means and for validating the one way analysis of variance test results for non-normal data in small sample size studies. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Mammographic breast density and breast cancer: evidence of a shared genetic basis.

PubMed

Varghese, Jajini S; Thompson, Deborah J; Michailidou, Kyriaki; Lindström, Sara; Turnbull, Clare; Brown, Judith; Leyland, Jean; Warren, Ruth M L; Luben, Robert N; Loos, Ruth J; Wareham, Nicholas J; Rommens, Johanna; Paterson, Andrew D; Martin, Lisa J; Vachon, Celine M; Scott, Christopher G; Atkinson, Elizabeth J; Couch, Fergus J; Apicella, Carmel; Southey, Melissa C; Stone, Jennifer; Li, Jingmei; Eriksson, Louise; Czene, Kamila; Boyd, Norman F; Hall, Per; Hopper, John L; Tamimi, Rulla M; Rahman, Nazneen; Easton, Douglas F

2012-03-15

Percent mammographic breast density (PMD) is a strong heritable risk factor for breast cancer. However, the pathways through which this risk is mediated are still unclear. To explore whether PMD and breast cancer have a shared genetic basis, we identified genetic variants most strongly associated with PMD in a published meta-analysis of five genome-wide association studies (GWAS) and used these to construct risk scores for 3,628 breast cancer cases and 5,190 controls from the UK2 GWAS of breast cancer. The signed per-allele effect estimates of single-nucleotide polymorphisms (SNP) were multiplied with the respective allele counts in the individual and summed over all SNPs to derive the risk score for an individual. These scores were included as the exposure variable in a logistic regression model with breast cancer case-control status as the outcome. This analysis was repeated using 10 different cutoff points for the most significant density SNPs (1%-10% representing 5,222-50,899 SNPs). Permutation analysis was also conducted across all 10 cutoff points. The association between risk score and breast cancer was significant for all cutoff points from 3% to 10% of top density SNPs, being most significant for the 6% (2-sided P = 0.002) to 10% (P = 0.001) cutoff points (overall permutation P = 0.003). Women in the top 10% of the risk score distribution had a 31% increased risk of breast cancer [OR = 1.31; 95% confidence interval (CI), 1.08-1.59] compared with women in the bottom 10%. Together, our results show that PMD and breast cancer have a shared genetic basis that is mediated through a large number of common variants.

Mammographic breast density and breast cancer: evidence of a shared genetic basis

PubMed Central

Varghese, Jajini S; Thompson, Deborah J; Michailidou, Kyriaki; Lindström, Sara; Turnbull, Clare; Brown, Judith; Leyland, Jean; Warren, Ruth ML; Luben, Robert N; Loos, Ruth J; Wareham, Nicholas J; Rommens, Johanna; Paterson, Andrew D; Martin, Lisa J; Vachon, Celine M; Scott, Christopher G; Atkinson, Elizabeth J; Couch, Fergus J; Apicella, Carmel; Southey, Melissa C; Stone, Jennifer; Li, Jingmei; Eriksson, Louise; Czene, Kamila; Boyd, Norman F; Hall, Per; Hopper, John L; Tamimi, Rulla M; Rahman, Nazneen; Easton, Douglas F

2012-01-01

Percent mammographic breast density (PMD) is a strong heritable risk factor for breast cancer. However, the pathways through which this risk is mediated are still unclear. To explore whether PMD and breast cancer have a shared genetic basis, we identified genetic variants most strongly associated with PMD in a published meta-analysis of five genome-wide association studies (GWAS) and used these to construct risk scores for 3628 breast cancer cases and 5190 controls from the UK2 GWAS of breast cancer. The signed per-allele effect estimates of SNPs were multiplied with the respective allele counts in the individual and summed over all SNPs to derive the risk score for an individual. These scores were included as the exposure variable in a logistic regression model with breast cancer case-control status as the outcome. This analysis was repeated using ten different cut-offs for the most significant density SNPs (1-10% representing 5,222-50,899 SNPs). Permutation analysis was also performed across all 10 cut-offs. The association between risk score and breast cancer was significant for all cut-offs from 3-10% of top density SNPs, being most significant for the 6% (2-sided P=0.002) to 10% (P=0.001) cut-offs (overall permutation P=0.003). Women in the top 10% of the risk score distribution had a 31% increased risk of breast cancer [OR= 1.31 (95%CI 1.08-1.59)] compared to women in the bottom 10%. Together, our results demonstrate that PMD and breast cancer have a shared genetic basis that is mediated through a large number of common variants. PMID:22266113

Multidimensional scaling analysis of financial time series based on modified cross-sample entropy methods

NASA Astrophysics Data System (ADS)

He, Jiayi; Shang, Pengjian; Xiong, Hui

2018-06-01

Stocks, as the concrete manifestation of financial time series with plenty of potential information, are often used in the study of financial time series. In this paper, we utilize the stock data to recognize their patterns through out the dissimilarity matrix based on modified cross-sample entropy, then three-dimensional perceptual maps of the results are provided through multidimensional scaling method. Two modified multidimensional scaling methods are proposed in this paper, that is, multidimensional scaling based on Kronecker-delta cross-sample entropy (MDS-KCSE) and multidimensional scaling based on permutation cross-sample entropy (MDS-PCSE). These two methods use Kronecker-delta based cross-sample entropy and permutation based cross-sample entropy to replace the distance or dissimilarity measurement in classical multidimensional scaling (MDS). Multidimensional scaling based on Chebyshev distance (MDSC) is employed to provide a reference for comparisons. Our analysis reveals a clear clustering both in synthetic data and 18 indices from diverse stock markets. It implies that time series generated by the same model are easier to have similar irregularity than others, and the difference in the stock index, which is caused by the country or region and the different financial policies, can reflect the irregularity in the data. In the synthetic data experiments, not only the time series generated by different models can be distinguished, the one generated under different parameters of the same model can also be detected. In the financial data experiment, the stock indices are clearly divided into five groups. Through analysis, we find that they correspond to five regions, respectively, that is, Europe, North America, South America, Asian-Pacific (with the exception of mainland China), mainland China and Russia. The results also demonstrate that MDS-KCSE and MDS-PCSE provide more effective divisions in experiments than MDSC.

Dynamic connectivity regression: Determining state-related changes in brain connectivity

PubMed Central

Cribben, Ivor; Haraldsdottir, Ragnheidur; Atlas, Lauren Y.; Wager, Tor D.; Lindquist, Martin A.

2014-01-01

Most statistical analyses of fMRI data assume that the nature, timing and duration of the psychological processes being studied are known. However, often it is hard to specify this information a priori. In this work we introduce a data-driven technique for partitioning the experimental time course into distinct temporal intervals with different multivariate functional connectivity patterns between a set of regions of interest (ROIs). The technique, called Dynamic Connectivity Regression (DCR), detects temporal change points in functional connectivity and estimates a graph, or set of relationships between ROIs, for data in the temporal partition that falls between pairs of change points. Hence, DCR allows for estimation of both the time of change in connectivity and the connectivity graph for each partition, without requiring prior knowledge of the nature of the experimental design. Permutation and bootstrapping methods are used to perform inference on the change points. The method is applied to various simulated data sets as well as to an fMRI data set from a study (N=26) of a state anxiety induction using a socially evaluative threat challenge. The results illustrate the method’s ability to observe how the networks between different brain regions changed with subjects’ emotional state. PMID:22484408

Estimation and Psychometric Analysis of Component Profile Scores via Multivariate Generalizability Theory

ERIC Educational Resources Information Center

Grochowalski, Joseph H.

2015-01-01

Component Universe Score Profile analysis (CUSP) is introduced in this paper as a psychometric alternative to multivariate profile analysis. The theoretical foundations of CUSP analysis are reviewed, which include multivariate generalizability theory and constrained principal components analysis. Because CUSP is a combination of generalizability…

A PSO-Based Hybrid Metaheuristic for Permutation Flowshop Scheduling Problems

PubMed Central

Zhang, Le; Wu, Jinnan

2014-01-01

This paper investigates the permutation flowshop scheduling problem (PFSP) with the objectives of minimizing the makespan and the total flowtime and proposes a hybrid metaheuristic based on the particle swarm optimization (PSO). To enhance the exploration ability of the hybrid metaheuristic, a simulated annealing hybrid with a stochastic variable neighborhood search is incorporated. To improve the search diversification of the hybrid metaheuristic, a solution replacement strategy based on the pathrelinking is presented to replace the particles that have been trapped in local optimum. Computational results on benchmark instances show that the proposed PSO-based hybrid metaheuristic is competitive with other powerful metaheuristics in the literature. PMID:24672389

A PSO-based hybrid metaheuristic for permutation flowshop scheduling problems.

PubMed

Zhang, Le; Wu, Jinnan

2014-01-01

This paper investigates the permutation flowshop scheduling problem (PFSP) with the objectives of minimizing the makespan and the total flowtime and proposes a hybrid metaheuristic based on the particle swarm optimization (PSO). To enhance the exploration ability of the hybrid metaheuristic, a simulated annealing hybrid with a stochastic variable neighborhood search is incorporated. To improve the search diversification of the hybrid metaheuristic, a solution replacement strategy based on the pathrelinking is presented to replace the particles that have been trapped in local optimum. Computational results on benchmark instances show that the proposed PSO-based hybrid metaheuristic is competitive with other powerful metaheuristics in the literature.

Palmprint verification using Lagrangian decomposition and invariant interest points

NASA Astrophysics Data System (ADS)

Gupta, P.; Rattani, A.; Kisku, D. R.; Hwang, C. J.; Sing, J. K.

2011-06-01

This paper presents a palmprint based verification system using SIFT features and Lagrangian network graph technique. We employ SIFT for feature extraction from palmprint images whereas the region of interest (ROI) which has been extracted from wide palm texture at the preprocessing stage, is considered for invariant points extraction. Finally, identity is established by finding permutation matrix for a pair of reference and probe palm graphs drawn on extracted SIFT features. Permutation matrix is used to minimize the distance between two graphs. The propsed system has been tested on CASIA and IITK palmprint databases and experimental results reveal the effectiveness and robustness of the system.

Index to Nuclear Safety: a technical progress review by chronology, permuted title, and author, Volume 18 (1) through Volume 22 (6)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cottrell, W.B.; Passiakos, M.

This index to Nuclear Safety covers articles published in Nuclear Safety, Volume 18, Number 1 (January-February 1977) through Volume 22, Number 6 (November-December 1981). The index is divided into three section: a chronological list of articles (including abstracts), a permuted-title (KWIC) index, and an author index. Nuclear Safety, a bimonthly technical progress review prepared by the Nuclear Safety Information Center, covers all safety aspects of nuclear power reactors and associated facilities. Over 300 technical articles published in Nuclear Safety in the last 5 years are listed in this index.

Non-Weyl asymptotics for quantum graphs with general coupling conditions

NASA Astrophysics Data System (ADS)

Davies, E. Brian; Exner, Pavel; Lipovský, Jiří

2010-11-01

Inspired by a recent result of Davies and Pushnitski, we study resonance asymptotics of quantum graphs with general coupling conditions at the vertices. We derive a criterion for the asymptotics to be of a non-Weyl character. We show that for balanced vertices with permutation-invariant couplings the asymptotics is non-Weyl only in the case of Kirchhoff or anti-Kirchhoff conditions. While for graphs without permutation symmetry numerous examples of non-Weyl behaviour can be constructed. Furthermore, we present an insight into what makes the Kirchhoff/anti-Kirchhoff coupling particular from the resonance point of view. Finally, we demonstrate a generalization to quantum graphs with unequal edge weights.

Diversification of Protein Cage Structure Using Circularly Permuted Subunits.

PubMed

Azuma, Yusuke; Herger, Michael; Hilvert, Donald

2018-01-17

Self-assembling protein cages are useful as nanoscale molecular containers for diverse applications in biotechnology and medicine. To expand the utility of such systems, there is considerable interest in customizing the structures of natural cage-forming proteins and designing new ones. Here we report that a circularly permuted variant of lumazine synthase, a cage-forming enzyme from Aquifex aeolicus (AaLS) affords versatile building blocks for the construction of nanocompartments that can be easily produced, tailored, and diversified. The topologically altered protein, cpAaLS, self-assembles into spherical and tubular cage structures with morphologies that can be controlled by the length of the linker connecting the native termini. Moreover, cpAaLS proteins integrate into wild-type and other engineered AaLS assemblies by coproduction in Escherichia coli to form patchwork cages. This coassembly strategy enables encapsulation of guest proteins in the lumen, modification of the exterior through genetic fusion, and tuning of the size and electrostatics of the compartments. This addition to the family of AaLS cages broadens the scope of this system for further applications and highlights the utility of circular permutation as a potentially general strategy for tailoring the properties of cage-forming proteins.

Structural redesign of lipase B from Candida antarctica by circular permutation and incremental truncation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Qian, Zhen; Horton, John R.; Cheng, Xiadong

2009-11-02

Circular permutation of Candida antarctica lipase B yields several enzyme variants with substantially increased catalytic activity. To better understand the structural and functional consequences of protein termini reorganization, we have applied protein engineering and x-ray crystallography to cp283, one of the most active hydrolase variants. Our initial investigation has focused on the role of an extended surface loop, created by linking the native N- and C-termini, on protein integrity. Incremental truncation of the loop partially compensates for observed losses in secondary structure and the permutants temperature of unfolding. Unexpectedly, the improvements are accompanied by quaternary-structure changes from monomer to dimer.more » The crystal structures of one truncated variant (cp283{Delta}7) in the apo-form determined at 1.49 {angstrom} resolution and with a bound phosphonate inhibitor at 1.69 {angstrom} resolution confirmed the formation of a homodimer by swapping of the enzyme's 35-residue N-terminal region. Separately, the new protein termini at amino acid positions 282/283 convert the narrow access tunnel to the catalytic triad into a broad crevice for accelerated substrate entry and product exit while preserving the native active-site topology for optimal catalytic turnover.« less

Conditional Bounds on Polarization Transfer

NASA Astrophysics Data System (ADS)

Nielsen, N. C.; Sorensen, O. W.

The implications of constraints on unitary transformations of spin operators with respect to the accessible regions of Liouville space are analyzed. Specifically, the effects of spin-permutation symmetry on the unitary propagators are investigated. The influence of S2 and S3 propagator symmetry on two-dimensional bounds for F z = Σ Ni=1 I iz ↔ G z = Σ Mj=1 S jz polarization transfer in IS and I 2S spin- {1}/{2} systems is examined in detail. One result is that the maximum achievable F z ↔ G z polarization transfer is not reduced by permutation symmetry among the spins. For I 2S spin systems, S3 symmetry in the unitary propagator is shown to significantly reduce the accessible region in the 2D F z-S z Liouville subspace compared to the case restricted by unitarity alone. That result is compared with transformations under symmetric dipolar and scalar J coupling as well as shift and RF interactions. An important practical implication is that the refined spin thermodynamic theory of Levitt, Suter, and Ernst ( J. Chem. Phys.84, 4243, 1986) for cross polarization in solid-state NMR does not predict experimental outcomes incompatible with constraints of unitarity and spin-permutation symmetry.

A hybrid quantum-inspired genetic algorithm for multiobjective flow shop scheduling.

PubMed

Li, Bin-Bin; Wang, Ling

2007-06-01

This paper proposes a hybrid quantum-inspired genetic algorithm (HQGA) for the multiobjective flow shop scheduling problem (FSSP), which is a typical NP-hard combinatorial optimization problem with strong engineering backgrounds. On the one hand, a quantum-inspired GA (QGA) based on Q-bit representation is applied for exploration in the discrete 0-1 hyperspace by using the updating operator of quantum gate and genetic operators of Q-bit. Moreover, random-key representation is used to convert the Q-bit representation to job permutation for evaluating the objective values of the schedule solution. On the other hand, permutation-based GA (PGA) is applied for both performing exploration in permutation-based scheduling space and stressing exploitation for good schedule solutions. To evaluate solutions in multiobjective sense, a randomly weighted linear-sum function is used in QGA, and a nondominated sorting technique including classification of Pareto fronts and fitness assignment is applied in PGA with regard to both proximity and diversity of solutions. To maintain the diversity of the population, two trimming techniques for population are proposed. The proposed HQGA is tested based on some multiobjective FSSPs. Simulation results and comparisons based on several performance metrics demonstrate the effectiveness of the proposed HQGA.

Permutation flow-shop scheduling problem to optimize a quadratic objective function

NASA Astrophysics Data System (ADS)

Ren, Tao; Zhao, Peng; Zhang, Da; Liu, Bingqian; Yuan, Huawei; Bai, Danyu

2017-09-01

A flow-shop scheduling model enables appropriate sequencing for each job and for processing on a set of machines in compliance with identical processing orders. The objective is to achieve a feasible schedule for optimizing a given criterion. Permutation is a special setting of the model in which the processing order of the jobs on the machines is identical for each subsequent step of processing. This article addresses the permutation flow-shop scheduling problem to minimize the criterion of total weighted quadratic completion time. With a probability hypothesis, the asymptotic optimality of the weighted shortest processing time schedule under a consistency condition (WSPT-CC) is proven for sufficiently large-scale problems. However, the worst case performance ratio of the WSPT-CC schedule is the square of the number of machines in certain situations. A discrete differential evolution algorithm, where a new crossover method with multiple-point insertion is used to improve the final outcome, is presented to obtain high-quality solutions for moderate-scale problems. A sequence-independent lower bound is designed for pruning in a branch-and-bound algorithm for small-scale problems. A set of random experiments demonstrates the performance of the lower bound and the effectiveness of the proposed algorithms.

SO(4) algebraic approach to the three-body bound state problem in two dimensions

NASA Astrophysics Data System (ADS)

Dmitrašinović, V.; Salom, Igor

2014-08-01

We use the permutation symmetric hyperspherical three-body variables to cast the non-relativistic three-body Schrödinger equation in two dimensions into a set of (possibly decoupled) differential equations that define an eigenvalue problem for the hyper-radial wave function depending on an SO(4) hyper-angular matrix element. We express this hyper-angular matrix element in terms of SO(3) group Clebsch-Gordan coefficients and use the latter's properties to derive selection rules for potentials with different dynamical/permutation symmetries. Three-body potentials acting on three identical particles may have different dynamical symmetries, in order of increasing symmetry, as follows: (1) S3 ⊗ OL(2), the permutation times rotational symmetry, that holds in sums of pairwise potentials, (2) O(2) ⊗ OL(2), the so-called "kinematic rotations" or "democracy symmetry" times rotational symmetry, that holds in area-dependent potentials, and (3) O(4) dynamical hyper-angular symmetry, that holds in hyper-radial three-body potentials. We show how the different residual dynamical symmetries of the non-relativistic three-body Hamiltonian lead to different degeneracies of certain states within O(4) multiplets.

A novel image encryption algorithm based on the chaotic system and DNA computing

NASA Astrophysics Data System (ADS)

Chai, Xiuli; Gan, Zhihua; Lu, Yang; Chen, Yiran; Han, Daojun

A novel image encryption algorithm using the chaotic system and deoxyribonucleic acid (DNA) computing is presented. Different from the traditional encryption methods, the permutation and diffusion of our method are manipulated on the 3D DNA matrix. Firstly, a 3D DNA matrix is obtained through bit plane splitting, bit plane recombination, DNA encoding of the plain image. Secondly, 3D DNA level permutation based on position sequence group (3DDNALPBPSG) is introduced, and chaotic sequences generated from the chaotic system are employed to permutate the positions of the elements of the 3D DNA matrix. Thirdly, 3D DNA level diffusion (3DDNALD) is given, the confused 3D DNA matrix is split into sub-blocks, and XOR operation by block is manipulated to the sub-DNA matrix and the key DNA matrix from the chaotic system. At last, by decoding the diffused DNA matrix, we get the cipher image. SHA 256 hash of the plain image is employed to calculate the initial values of the chaotic system to avoid chosen plaintext attack. Experimental results and security analyses show that our scheme is secure against several known attacks, and it can effectively protect the security of the images.

A novel chaos-based image encryption algorithm using DNA sequence operations

NASA Astrophysics Data System (ADS)

Chai, Xiuli; Chen, Yiran; Broyde, Lucie

2017-01-01

An image encryption algorithm based on chaotic system and deoxyribonucleic acid (DNA) sequence operations is proposed in this paper. First, the plain image is encoded into a DNA matrix, and then a new wave-based permutation scheme is performed on it. The chaotic sequences produced by 2D Logistic chaotic map are employed for row circular permutation (RCP) and column circular permutation (CCP). Initial values and parameters of the chaotic system are calculated by the SHA 256 hash of the plain image and the given values. Then, a row-by-row image diffusion method at DNA level is applied. A key matrix generated from the chaotic map is used to fuse the confused DNA matrix; also the initial values and system parameters of the chaotic system are renewed by the hamming distance of the plain image. Finally, after decoding the diffused DNA matrix, we obtain the cipher image. The DNA encoding/decoding rules of the plain image and the key matrix are determined by the plain image. Experimental results and security analyses both confirm that the proposed algorithm has not only an excellent encryption result but also resists various typical attacks.

Searching for the fastest dynamo: laminar ABC flows.

PubMed

Alexakis, Alexandros

2011-08-01

The growth rate of the dynamo instability as a function of the magnetic Reynolds number R(M) is investigated by means of numerical simulations for the family of the Arnold-Beltrami-Childress (ABC) flows and for two different forcing scales. For the ABC flows that are driven at the largest available length scale, it is found that, as the magnetic Reynolds number is increased: (a) The flow that results first in a dynamo is the 2 1/2-dimensional flow for which A=B and C=0 (and all permutations). (b) The second type of flow that results in a dynamo is the one for which A=B≃2C/5 (and permutations). (c) The most symmetric flow, A=B=C, is the third type of flow that results in a dynamo. (d) As R(M) is increased, the A=B=C flow stops being a dynamo and transitions from a local maximum to a third-order saddle point. (e) At larger R(M), the A=B=C flow reestablishes itself as a dynamo but remains a saddle point. (f) At the largest examined R(M), the growth rate of the 2 1/2-dimensional flows starts to decay, the A=B=C flow comes close to a local maximum again, and the flow A=B≃2C/5 (and permutations) results in the fastest dynamo with growth rate γ≃0.12 at the largest examined R(M). For the ABC flows that are driven at the second largest available length scale, it is found that (a) the 2 1/2-dimensional flows A=B,C=0 (and permutations) are again the first flows that result in a dynamo with a decreased onset. (b) The most symmetric flow, A=B=C, is the second type of flow that results in a dynamo. It is, and it remains, a local maximum. (c) At larger R(M), the flow A=B≃2C/5 (and permutations) appears as the third type of flow that results in a dynamo. As R(M) is increased, it becomes the flow with the largest growth rate. The growth rates appear to have some correlation with the Lyapunov exponents, but constructive refolding of the field lines appears equally important in determining the fastest dynamo flow.

Detecting changes resulting from human pressure in a naturally quick-changing and heterogeneous environment: Spatial and temporal scales of variability in coastal lagoons

NASA Astrophysics Data System (ADS)

Pérez-Ruzafa, A.; Marcos, C.; Pérez-Ruzafa, I. M.; Barcala, E.; Hegazi, M. I.; Quispe, J.

2007-10-01

To detect changes in ecosystems due to human impact, experimental designs must include replicates at the appropriate scale to avoid pseudoreplication. Although coastal lagoons, with their highly variable environmental factors and biological assemblages, are relatively well-studied systems, very little is known about their natural scales of variation. In this study, we investigate the spatio-temporal scales of variability in the Mar Menor coastal lagoon (SE Spain) using structured hierarchical sampling designs, mixed and permutational multi-variate analyses of variance, and ordination multi-variate analyses applied to hydrographical parameters, nutrients, chlorophyll a and ichthyoplankton in the water column, and to macrophyte and fish benthic assemblages. Lagoon processes in the Mar Menor show heterogeneous patterns at different temporal and spatial scales. The water column characteristics (including nutrient concentration) showed small-scale spatio-temporal variability, from 10 0 to 10 1 km and from fortnightly to seasonally. Biological features (chlorophyll a concentration and ichthyoplankton assemblage descriptors) showed monthly changes and spatial patterns at the scale of 10 0 (chlorophyll a) - 10 1 km (ichthyoplankton). Benthic assemblages (macrophytes and fishes) showed significant differences between types of substrates in the same locality and between localities, according to horizontal gradients related with confinement in the lagoon, at the scale of 10 0-10 1 km. The vertical zonation of macrophyte assemblages (at scales of 10 1-10 2 cm) overlaps changes in substrata and horizontal gradients. Seasonal patterns in vegetation biomass were not significant, but the significant interaction between Locality and Season indicated that the seasons of maximum and minimum biomass depend on local environmental conditions. Benthic fish assemblages showed no significant patterns at the monthly scale but did show seasonal patterns.

Graph characterization via Ihara coefficients.

PubMed

Ren, Peng; Wilson, Richard C; Hancock, Edwin R

2011-02-01

The novel contributions of this paper are twofold. First, we demonstrate how to characterize unweighted graphs in a permutation-invariant manner using the polynomial coefficients from the Ihara zeta function, i.e., the Ihara coefficients. Second, we generalize the definition of the Ihara coefficients to edge-weighted graphs. For an unweighted graph, the Ihara zeta function is the reciprocal of a quasi characteristic polynomial of the adjacency matrix of the associated oriented line graph. Since the Ihara zeta function has poles that give rise to infinities, the most convenient numerically stable representation is to work with the coefficients of the quasi characteristic polynomial. Moreover, the polynomial coefficients are invariant to vertex order permutations and also convey information concerning the cycle structure of the graph. To generalize the representation to edge-weighted graphs, we make use of the reduced Bartholdi zeta function. We prove that the computation of the Ihara coefficients for unweighted graphs is a special case of our proposed method for unit edge weights. We also present a spectral analysis of the Ihara coefficients and indicate their advantages over other graph spectral methods. We apply the proposed graph characterization method to capturing graph-class structure and clustering graphs. Experimental results reveal that the Ihara coefficients are more effective than methods based on Laplacian spectra.

A tight and explicit representation of Q in sparse QR factorization

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ng, E.G.; Peyton, B.W.

1992-05-01

In QR factorization of a sparse m{times}n matrix A (m {ge} n) the orthogonal factor Q is often stored implicitly as a lower trapezoidal matrix H known as the Householder matrix. This paper presents a simple characterization of the row structure of Q, which could be used as the basis for a sparse data structure that can store Q explicitly. The new characterization is a simple extension of a well known row-oriented characterization of the structure of H. Hare, Johnson, Olesky, and van den Driessche have recently provided a complete sparsity analysis of the QR factorization. Let U be themore » matrix consisting of the first n columns of Q. Using results from, we show that the data structures for H and U resulting from our characterizations are tight when A is a strong Hall matrix. We also show that H and the lower trapezoidal part of U have the same sparsity characterization when A is strong Hall. We then show that this characterization can be extended to any weak Hall matrix that has been permuted into block upper triangular form. Finally, we show that permuting to block triangular form never increases the fill incurred during the factorization.« less

An investigation of sex differences in acoustic features in black-capped chickadee (Poecile atricapillus) chick-a-dee calls.

PubMed

Campbell, Kimberley A; Hahn, Allison H; Congdon, Jenna V; Sturdy, Christopher B

2016-09-01

Sex differences have been identified in a number of black-capped chickadee vocalizations and in the chick-a-dee calls of other chickadee species [i.e., Carolina chickadees (Poecile carolinensis)]. In the current study, 12 acoustic features in black-capped chickadee chick-a-dee calls were investigated, including both frequency and duration measurements. Using permuted discriminant function analyses, these features were examined to determine if any features could be used to identify the sex of the caller. Only one note type (A notes) classified male and female calls at levels approaching significance. In particular, a permuted discriminant function analysis revealed that the start frequency of A notes best allowed for categorization between the sexes compared to any other acoustic parameter. This finding is consistent with previous research on Carolina chickadee chick-a-dee calls that found that the starting frequency differed between male- and female-produced A notes [Freeberg, Lucas, and Clucas (2003). J. Acoust. Soc. Am. 113, 2127-2136]. Taken together, these results and the results of studies with other chickadee species suggest that sex differences likely exist in the chick-a-dee call, specifically acoustic features in A notes, but that more complex features than those addressed here may be associated with the sex of the caller.

Robust inference from multiple test statistics via permutations: a better alternative to the single test statistic approach for randomized trials.

PubMed

Ganju, Jitendra; Yu, Xinxin; Ma, Guoguang Julie

2013-01-01

Formal inference in randomized clinical trials is based on controlling the type I error rate associated with a single pre-specified statistic. The deficiency of using just one method of analysis is that it depends on assumptions that may not be met. For robust inference, we propose pre-specifying multiple test statistics and relying on the minimum p-value for testing the null hypothesis of no treatment effect. The null hypothesis associated with the various test statistics is that the treatment groups are indistinguishable. The critical value for hypothesis testing comes from permutation distributions. Rejection of the null hypothesis when the smallest p-value is less than the critical value controls the type I error rate at its designated value. Even if one of the candidate test statistics has low power, the adverse effect on the power of the minimum p-value statistic is not much. Its use is illustrated with examples. We conclude that it is better to rely on the minimum p-value rather than a single statistic particularly when that single statistic is the logrank test, because of the cost and complexity of many survival trials. Copyright © 2013 John Wiley & Sons, Ltd.

Permutation modulation for quantization and information reconciliation in CV-QKD systems

NASA Astrophysics Data System (ADS)

Daneshgaran, Fred; Mondin, Marina; Olia, Khashayar

2017-08-01

This paper is focused on the problem of Information Reconciliation (IR) for continuous variable Quantum Key Distribution (QKD). The main problem is quantization and assignment of labels to the samples of the Gaussian variables observed at Alice and Bob. Trouble is that most of the samples, assuming that the Gaussian variable is zero mean which is de-facto the case, tend to have small magnitudes and are easily disturbed by noise. Transmission over longer and longer distances increases the losses corresponding to a lower effective Signal to Noise Ratio (SNR) exasperating the problem. Here we propose to use Permutation Modulation (PM) as a means of quantization of Gaussian vectors at Alice and Bob over a d-dimensional space with d ≫ 1. The goal is to achieve the necessary coding efficiency to extend the achievable range of continuous variable QKD by quantizing over larger and larger dimensions. Fractional bit rate per sample is easily achieved using PM at very reasonable computational cost. Ordered statistics is used extensively throughout the development from generation of the seed vector in PM to analysis of error rates associated with the signs of the Gaussian samples at Alice and Bob as a function of the magnitude of the observed samples at Bob.

FieldTrip: Open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data.

PubMed

Oostenveld, Robert; Fries, Pascal; Maris, Eric; Schoffelen, Jan-Mathijs

2011-01-01

This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages.

Multivariate meta-analysis: potential and promise.

PubMed

Jackson, Dan; Riley, Richard; White, Ian R

2011-09-10

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day 'Multivariate meta-analysis' event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rouxelin, Pascal Nicolas; Strydom, Gerhard

Best-estimate plus uncertainty analysis of reactors is replacing the traditional conservative (stacked uncertainty) method for safety and licensing analysis. To facilitate uncertainty analysis applications, a comprehensive approach and methodology must be developed and applied. High temperature gas cooled reactors (HTGRs) have several features that require techniques not used in light-water reactor analysis (e.g., coated-particle design and large graphite quantities at high temperatures). The International Atomic Energy Agency has therefore launched the Coordinated Research Project on HTGR Uncertainty Analysis in Modeling to study uncertainty propagation in the HTGR analysis chain. The benchmark problem defined for the prismatic design is represented bymore » the General Atomics Modular HTGR 350. The main focus of this report is the compilation and discussion of the results obtained for various permutations of Exercise I 2c and the use of the cross section data in Exercise II 1a of the prismatic benchmark, which is defined as the last and first steps of the lattice and core simulation phases, respectively. The report summarizes the Idaho National Laboratory (INL) best estimate results obtained for Exercise I 2a (fresh single-fuel block), Exercise I 2b (depleted single-fuel block), and Exercise I 2c (super cell) in addition to the first results of an investigation into the cross section generation effects for the super-cell problem. The two dimensional deterministic code known as the New ESC based Weighting Transport (NEWT) included in the Standardized Computer Analyses for Licensing Evaluation (SCALE) 6.1.2 package was used for the cross section evaluation, and the results obtained were compared to the three dimensional stochastic SCALE module KENO VI. The NEWT cross section libraries were generated for several permutations of the current benchmark super-cell geometry and were then provided as input to the Phase II core calculation of the stand alone neutronics Exercise II 1a. The steady state core calculations were simulated with the INL coupled-code system known as the Parallel and Highly Innovative Simulation for INL Code System (PHISICS) and the system thermal-hydraulics code known as the Reactor Excursion and Leak Analysis Program (RELAP) 5 3D using the nuclear data libraries previously generated with NEWT. It was observed that significant differences in terms of multiplication factor and neutron flux exist between the various permutations of the Phase I super-cell lattice calculations. The use of these cross section libraries only leads to minor changes in the Phase II core simulation results for fresh fuel but shows significantly larger discrepancies for spent fuel cores. Furthermore, large incongruities were found between the SCALE NEWT and KENO VI results for the super cells, and while some trends could be identified, a final conclusion on this issue could not yet be reached. This report will be revised in mid 2016 with more detailed analyses of the super-cell problems and their effects on the core models, using the latest version of SCALE (6.2). The super-cell models seem to show substantial improvements in terms of neutron flux as compared to single-block models, particularly at thermal energies.« less

Double symbolic joint entropy in nonlinear dynamic complexity analysis

NASA Astrophysics Data System (ADS)

Yao, Wenpo; Wang, Jun

2017-07-01

Symbolizations, the base of symbolic dynamic analysis, are classified as global static and local dynamic approaches which are combined by joint entropy in our works for nonlinear dynamic complexity analysis. Two global static methods, symbolic transformations of Wessel N. symbolic entropy and base-scale entropy, and two local ones, namely symbolizations of permutation and differential entropy, constitute four double symbolic joint entropies that have accurate complexity detections in chaotic models, logistic and Henon map series. In nonlinear dynamical analysis of different kinds of heart rate variability, heartbeats of healthy young have higher complexity than those of the healthy elderly, and congestive heart failure (CHF) patients are lowest in heartbeats' joint entropy values. Each individual symbolic entropy is improved by double symbolic joint entropy among which the combination of base-scale and differential symbolizations have best complexity analysis. Test results prove that double symbolic joint entropy is feasible in nonlinear dynamic complexity analysis.

Acclimation and Institutionalization of the Mouse Microbiota Following Transportation

PubMed Central

Montonye, Dan R.; Ericsson, Aaron C.; Busi, Susheel B.; Lutz, Cathleen; Wardwell, Keegan; Franklin, Craig L.

2018-01-01

Using animal models, the gut microbiota has been shown to play a critical role in the health and disease of many organ systems. Unfortunately, animal model studies often lack reproducibility when performed at different institutions. Previous studies in our laboratory have shown that the gut microbiota of mice can vary with a number of husbandry factors leading us to speculate that differing environments may alter gut microbiota, which in turn may influence animal model phenotypes. As an extension of these studies, we hypothesized that the shipping of mice from a mouse producer to an institution will result in changes in the type, relative abundance, and functional composition of the gut microbiota. Furthermore, we hypothesized that mice will develop a microbiota unique to the institution and facility in which they are housed. To test these hypotheses, mice of two strains (C57BL/6J and BALB/cJ), two age groups (4 week and 8 week old), and originating from two types of housing (research animal facility under conventional housing and production facilities under maximum barrier housing) were obtained from The Jackson Laboratory. Fecal samples were collected the day prior to shipping, immediately upon arrival, and then on days 2, 5, 7, and weeks 2, 4, and 9 post-arrival. Following the first post-arrival fecal collection, mice were separated into 2 groups and housed at different facilities at our institution while keeping their caging, diet, and husbandry practices the same. DNA was extracted from the collected fecal pellets and 16S rRNA amplicons were sequenced in order to characterize the type and relative abundance of gut bacteria. Principal component analysis (PCA) and permutational multivariate analysis of variance (PERMANOVA) demonstrated that both the shipping and the institution and facility in which mice were housed altered the gut microbiota. Phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) predicted differences in functional composition in the gut microbiota of mice based on time of acclimation. PMID:29892276

Acclimation and Institutionalization of the Mouse Microbiota Following Transportation.

PubMed

Montonye, Dan R; Ericsson, Aaron C; Busi, Susheel B; Lutz, Cathleen; Wardwell, Keegan; Franklin, Craig L

2018-01-01

Using animal models, the gut microbiota has been shown to play a critical role in the health and disease of many organ systems. Unfortunately, animal model studies often lack reproducibility when performed at different institutions. Previous studies in our laboratory have shown that the gut microbiota of mice can vary with a number of husbandry factors leading us to speculate that differing environments may alter gut microbiota, which in turn may influence animal model phenotypes. As an extension of these studies, we hypothesized that the shipping of mice from a mouse producer to an institution will result in changes in the type, relative abundance, and functional composition of the gut microbiota. Furthermore, we hypothesized that mice will develop a microbiota unique to the institution and facility in which they are housed. To test these hypotheses, mice of two strains (C57BL/6J and BALB/cJ), two age groups (4 week and 8 week old), and originating from two types of housing (research animal facility under conventional housing and production facilities under maximum barrier housing) were obtained from The Jackson Laboratory. Fecal samples were collected the day prior to shipping, immediately upon arrival, and then on days 2, 5, 7, and weeks 2, 4, and 9 post-arrival. Following the first post-arrival fecal collection, mice were separated into 2 groups and housed at different facilities at our institution while keeping their caging, diet, and husbandry practices the same. DNA was extracted from the collected fecal pellets and 16S rRNA amplicons were sequenced in order to characterize the type and relative abundance of gut bacteria. Principal component analysis (PCA) and permutational multivariate analysis of variance (PERMANOVA) demonstrated that both the shipping and the institution and facility in which mice were housed altered the gut microbiota. Phylogenetic investigation of communities by reconstruction of unobserved states (PICRUSt) predicted differences in functional composition in the gut microbiota of mice based on time of acclimation.

Brief Report: Dialister as a Microbial Marker of Disease Activity in Spondyloarthritis.

PubMed

Tito, Raul Y; Cypers, Heleen; Joossens, Marie; Varkas, Gaëlle; Van Praet, Liesbet; Glorieus, Elien; Van den Bosch, Filip; De Vos, Martine; Raes, Jeroen; Elewaut, Dirk

2017-01-01

Dysbiosis of the intestinal microbiota has been widely established in inflammatory bowel disease (IBD). There is significant clinical and genetic overlap between spondyloarthritis (SpA) and IBD, and up to 50% of all patients with SpA exhibit microscopic signs of bowel inflammation, often bearing particular resemblance to early Crohn's disease, a subtype of IBD. This study was undertaken to assess the relationship between intestinal microbial composition, gut histology, and disease activity markers in SpA. Gene analysis by 16S ribosomal RNA amplicon sequencing was used to compare the microbial composition in ileal and colonic biopsy specimens from 27 patients with SpA (14 with microscopic bowel inflammation, 13 without) and 15 healthy control subjects (ileal samples from all 15 subjects and colonic samples from 6). Spearman's rank correlation tests were used to assess correlations of the microbial composition with disease activity measures. The intestinal inflammation status (histologically normal versus acute or chronic inflammation) was strongly associated with the mucosal microbiota profile of patients with SpA. In inflamed biopsy tissue, the detected bacterial community composition clustered separately from that in noninflamed biopsy tissue (P < 0.05 by permutational multivariate analysis of variance, using hierarchical clustering on Bray-Curtis distances). Interestingly, abundance of the genus Dialister was found to be positively correlated with the Ankylosing Spondylitis Disease Activity Score (Spearman's rho = 0.62, false discovery rate-corrected q < 0.01). This finding was further supported by the low frequency of Dialister observed in noninflamed ileal and colonic biopsy tissue from patients with SpA and healthy controls. These findings demonstrate a significant difference in the intestinal microbial composition in patients with SpA who have microscopic gut inflammation compared to those without microscopic gut inflammation. Moreover, Dialister may represent a potential microbial marker of disease activity in SpA. © 2016, American College of Rheumatology.

Spatial variability in distribution and prevalence of Caribbean scleractinian coral and octocoral diseases. II. Genera-level analysis.

PubMed

Cróquer, Aldo; Weil, Ernesto

2009-02-25

Geographic assessments of coral/octocoral diseases affecting major reef-building genera and abundant reef species are important to understand their local and geographic spatial-temporal variability and their impact. The status and spatial variability of major Caribbean coral/octocoral diseases affecting important reef-building coral (Montastraea, Diploria, Siderastrea, Stephanocoenia, Porites, and Agaricia) and common, widespread octocoral genera (Gorgonia and Pseudopterogorgia) was assessed along 4 permanent 10 x 2 m band-transects in each of 3 depth habitats (<4, 5-12 and >15 m) on 2 reefs in 6 countries across the wider Caribbean during the summer and fall of 2005. A permutational multivariate analysis of variance was used to test the spatial variability (countries, reef sites and depth habitats) in prevalence of major diseases in these genera. We found a significant interaction of disease prevalence in the different coral and octocoral genera between reef sites and habitats (depth intervals). Montastraea was primarily affected by both white plague (WP-II) and yellow band disease in deep (16.9 +/- SE 16% and 16.9 +/- SE 2.3%) and intermediate (8.1 +/- SE 1.6% and 15.5 +/- SE 2.3%) depth habitats of Culebrita (Puerto Rico) and Chub Cut (Bermuda), respectively. Prevalence of multiple diseases simultaneously and other compromised-health problems affecting Montastraea colonies varied between 0.2 to 2% and 0.2 to 1.8%, respectively. Agaricia and Diploria were mostly affected by WP-II (0.5 to 16%), black band disease (0.4 to 5%) and Caribbean ciliate infections (0.2 to 12%). Siderastrea and Stephanocoenia were mainly affected by dark spots disease in Curaçao, with higher prevalence in intermediate (40.5 +/- SE 6.2%) and deep (26.6 +/- SE 4.2%) habitats. Aspergillosis and other compromised-health conditions affected Gorgonia ventalina (0.2 to 8%) and other common and widespread octocoral genera (1 to 14%), respectively.

SSU rDNA sequence diversity and seasonally differentiated distribution of nanoplanktonic ciliates in neritic Bohai and Yellow Seas as revealed by T-RFLP.

PubMed

Dong, Jun; Shi, Fei; Li, Han; Zhang, Xiaoming; Hu, Xiaozhong; Gong, Jun

2014-01-01

Nanociliates have been frequently found to be important players in the marine microbial loop, however, little is known about their diversity and distribution in coastal ecosystems. We investigated the molecular diversity and distribution patterns of nanoplanktonic oligotrich and choreotrich (OC) ciliates in surface water of three neritic basins of northern China, the South Yellow Sea (SYS), North Yellow Sea (NYS), and Bohai Sea (BS) in June and November 2011. SSU rRNA gene clone libraries generated from three summertime samples (sites B38, B4 and H8) were analyzed and revealed a large novel ribotype diversity, of which many were low-abundant phylotypes belonging to the subclass Oligotrichia, but divergent from described morphospecies. Based on the data of terminal-restriction fragment length polymorphism (T-RFLP) analysis of all 35 samples, we found that the T-RF richness was generally higher in the SYS than in the BS, and negatively correlated with the molar ratio of P to Si. Overall, multidimensional scaling and permutational multivariate analysis of variance of the community turnover demonstrated a distinct seasonal pattern but no basin-to-basin differentiation across all samples. Nevertheless, significant community differences among basins were recognized in the winter dataset. Mantel tests showed that the environmental factors, P:Si ratio, water temperature and concentration of dissolved oxygen (DO), determined the community across all samples. However, both biogeographic distance and environment shaped the community in winter, with DO being the most important physicochemical factor. Our results indicate that the stoichiometric ratio of P:Si is a key factor, through which the phytoplankton community may be shaped, resulting in a cascade effect on the diversity and community composition of OC nanociliates in the N-rich, Si-limited coastal surface waters, and that the Yellow Sea Warm Current drives the nanociliate community, and possibly the microbial food webs, in the coastal ecosystem in winter.

Uneven-aged silviculture can enhance within stand heterogeneity and beetle diversity.

PubMed

Joelsson, Klara; Hjältén, Joakim; Work, Timothy

2018-01-01

Uneven-aged silviculture may better maintain species assemblages associated with old-growth forests than clear felling in part due to habitat heterogeneity created by maintaining standing retention strips adjacent to harvest trails. Retention strips and harvest trails created at the time of tree removal will likely have different microclimate and may harbor different assemblages. In some cases, the resultant stand heterogeneity associated with uneven-aged silviculture may be similar to natural small-scale disturbances. For beetles, increased light and temperature as well as potential access to young vegetation and deadwood substrates present in harvset trails may harbor beetle assemblages similar to those found in natural gaps. We sampled saproxylic beetles using flight intercept traps placed in harvest corridors and retention strips in 9 replicated uneven-aged spruce stands in central Sweden. We compared abundance, species richness and composition between harvest corridors and retention strips using generalized linear models, rarefaction, permutational multivariate analysis of variance and indicator species analysis. Canopy openness doubled, mean temperature and variability in daily temperature increased and humidity decreased on harvest trails. Beetle richness and abundance were greater in harvests trails than in retention strips and the beetle species composition differed significantly between habitats. Twenty-five species were associated with harvest trails, including three old-growth specialists such as Agathidium discoideum (Erichson), currently red-listed. We observed only one species, Xylechinus pilosus (Ratzeburg) that strongly favored retention strips. Harvest trails foster both open habitat species and old-growth species while retention strips harbored forest interior specialists. The combination of closed canopy, stratified forest in the retention strips and gap-like conditions on the harvest trails thus increases overall species richness and maintains more diverse assemblages at the stand level than would otherwise be seen in less heterogeneous stand types. This suggests that uneven-aged silviculture may provide added conservation benefits for both open habitat and old-growth specialists than silvicultural approaches that reduce stand heterogeneity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multivariate Models for Normal and Binary Responses in Intervention Studies

ERIC Educational Resources Information Center

Pituch, Keenan A.; Whittaker, Tiffany A.; Chang, Wanchen

2016-01-01

Use of multivariate analysis (e.g., multivariate analysis of variance) is common when normally distributed outcomes are collected in intervention research. However, when mixed responses--a set of normal and binary outcomes--are collected, standard multivariate analyses are no longer suitable. While mixed responses are often obtained in…

Directional genetic selection by pulp mill effluent on multiple natural populations of three-spined stickleback (Gasterosteus aculeatus).

PubMed

Lind, Emma E; Grahn, Mats

2011-05-01

Contamination can cause a rapid environmental change which may require populations to respond with evolutionary changes. To evaluate the effects of pulp mill effluents on population genetics, we sampled three-spined sticklebacks (Gasterosteus aculeatus) near four pulp mills and four adjacent reference sites and analyzed Amplified Fragment Length Polymorphism (AFLP) to compare genetic variability. A fine scale genetic structure was detected and samples from polluted sites separated from reference sites in multidimensional scaling plots (P<0.005, 1000 permutations) and locus-by-locus Analysis of Molecular Variance (AMOVA) further confirmed that habitats are significantly separated (F(ST)=0.021, P<0.01, 1023 permutations). The amount of genetic variation between populations did not differ between habitats, and populations from both habitats had similar levels of heterozygosity (polluted sites Nei's Hs=0.11, reference sites Nei's Hs=0.11). Still, pairwise F(ST): s between three, out of four, pairs of polluted-reference sites were significant. A F(ST)-outlier analysis showed that 21 (8.4%) loci were statistically different from a neutral distribution at the P<0.05 level and therefore indicated to be under divergent selection. When removing 13 F(ST)-outlier loci, significant at the P<0.01 level, differentiation between habitats disappeared in a multidimensional scaling plot. In conclusion, pulp mill effluence has acted as a selective agent on natural populations of G. aculeatus, causing a convergence in genotype composition change at multiple sites in an open environment. © The Author(s) 2011. This article is published with open access at Springerlink.com

Do two and three year old children use an incremental first-NP-as-agent bias to process active transitive and passive sentences?: A permutation analysis

PubMed Central

Chang, Franklin; Rowland, Caroline; Ferguson, Heather; Pine, Julian

2017-01-01

We used eye-tracking to investigate if and when children show an incremental bias to assume that the first noun phrase in a sentence is the agent (first-NP-as-agent bias) while processing the meaning of English active and passive transitive sentences. We also investigated whether children can override this bias to successfully distinguish active from passive sentences, after processing the remainder of the sentence frame. For this second question we used eye-tracking (Study 1) and forced-choice pointing (Study 2). For both studies, we used a paradigm in which participants simultaneously saw two novel actions with reversed agent-patient relations while listening to active and passive sentences. We compared English-speaking 25-month-olds and 41-month-olds in between-subjects sentence structure conditions (Active Transitive Condition vs. Passive Condition). A permutation analysis found that both age groups showed a bias to incrementally map the first noun in a sentence onto an agent role. Regarding the second question, 25-month-olds showed some evidence of distinguishing the two structures in the eye-tracking study. However, the 25-month-olds did not distinguish active from passive sentences in the forced choice pointing task. In contrast, the 41-month-old children did reanalyse their initial first-NP-as-agent bias to the extent that they clearly distinguished between active and passive sentences both in the eye-tracking data and in the pointing task. The results are discussed in relation to the development of syntactic (re)parsing. PMID:29049390

Associations between bacterial communities of house dust and infant gut

DOE Office of Scientific and Technical Information (OSTI.GOV)

Konya, T.; Koster, B.; Maughan, H.

The human gut is host to a diverse and abundant community of bacteria that influence health and disease susceptibility. This community develops in infancy, and its composition is strongly influenced by environmental factors, notably perinatal anthropogenic exposures such as delivery mode (Cesarean vs. vaginal) and feeding method (breast vs. formula); however, the built environment as a possible source of exposure has not been considered. Here we report on a preliminary investigation of the associations between bacteria in house dust and the nascent fecal microbiota from 20 subjects from the Canadian Healthy Infant Longitudinal Development (CHILD) Study using high-throughput sequence analysismore » of portions of the 16S rRNA gene. Despite significant differences between the dust and fecal microbiota revealed by Nonmetric Multidimensional Scaling (NMDS) analysis, permutation analysis confirmed that 14 bacterial OTUs representing the classes Actinobacteria (3), Bacilli (3), Clostridia (6) and Gammaproteobacteria (2) co-occurred at a significantly higher frequency in matched dust–stool pairs than in randomly permuted pairs, indicating an association between these dust and stool communities. These associations could indicate a role for the indoor environment in shaping the nascent gut microbiota, but future studies will be needed to confirm that our findings do not solely reflect a reverse pathway. Although pet ownership was strongly associated with the presence of certain genera in the dust for dogs (Agrococcus, Carnobacterium, Exiguobacterium, Herbaspirillum, Leifsonia and Neisseria) and cats (Escherichia), no clear patterns were observed in the NMDS-resolved stool community profiles as a function of pet ownership.« less

ON THE NUMBER OF SOLUTIONS OF THE EQUATION x^k = a IN THE SYMMETRIC GROUP S_n

NASA Astrophysics Data System (ADS)

Pavlov, A. I.

1981-04-01

This paper consists of three sections. In the first a formula is given for the number N_n^{(k)}(a) of solutions of the equation x^k = a in S_n depending on the cyclic structure of the permutation a. In the second an asymptotic formula is given for the quantity M_n^{(k)} = \\max_{a \\in S_n} N_n^{(k)}(a) for a fixed k \\geq 2 as n \\to \\infty. In the third an asymptotic formula is found for the cardinality of the set of permutations a such that the equation x^k = a has a unique solution. Bibliography: 5 titles.

Approximate strip exchanging.

PubMed

Roy, Swapnoneel; Thakur, Ashok Kumar

2008-01-01

Genome rearrangements have been modelled by a variety of primitives such as reversals, transpositions, block moves and block interchanges. We consider such a genome rearrangement primitive Strip Exchanges. Given a permutation, the challenge is to sort it by using minimum number of strip exchanges. A strip exchanging move interchanges the positions of two chosen strips so that they merge with other strips. The strip exchange problem is to sort a permutation using minimum number of strip exchanges. We present here the first non-trivial 2-approximation algorithm to this problem. We also observe that sorting by strip-exchanges is fixed-parameter-tractable. Lastly we discuss the application of strip exchanges in a different area Optical Character Recognition (OCR) with an example.

On the representation matrices of the spin permutation group. [for atomic and molecular electronic structures

NASA Technical Reports Server (NTRS)

Wilson, S.

1977-01-01

A method is presented for the determination of the representation matrices of the spin permutation group (symmetric group), a detailed knowledge of these matrices being required in the study of the electronic structure of atoms and molecules. The method is characterized by the use of two different coupling schemes. Unlike the Yamanouchi spin algebraic scheme, the method is not recursive. The matrices for the fundamental transpositions can be written down directly in one of the two bases. The method results in a computationally significant reduction in the number of matrix elements that have to be stored when compared with, say, the standard Young tableaux group theoretical approach.

Compositionally and functionally distinct sinus microbiota in chronic rhinosinusitis patients have immunological and clinically divergent consequences.

PubMed

Cope, Emily K; Goldberg, Andrew N; Pletcher, Steven D; Lynch, Susan V

2017-05-12

Chronic rhinosinusitis (CRS) is a heterogeneous disease characterized by persistent sinonasal inflammation and sinus microbiome dysbiosis. The basis of this heterogeneity is poorly understood. We sought to address the hypothesis that a limited number of compositionally distinct pathogenic bacterial microbiota exist in CRS patients and invoke discrete immune responses and clinical phenotypes in CRS patients. Sinus brushings from patients with CRS (n = 59) and healthy individuals (n = 10) collected during endoscopic sinus surgery were analyzed using 16S rRNA gene sequencing, predicted metagenomics, and RNA profiling of the mucosal immune response. We show that CRS patients cluster into distinct sub-groups (DSI-III), each defined by specific pattern of bacterial co-colonization (permutational multivariate analysis of variance (PERMANOVA); p = 0.001, r 2  = 0.318). Each sub-group was typically dominated by a pathogenic family: Streptococcaceae (DSI), Pseudomonadaceae (DSII), Corynebacteriaceae [DSIII(a)], or Staphylococcaceae [DSIII(b)]. Each pathogenic microbiota was predicted to be functionally distinct (PERMANOVA; p = 0.005, r 2  = 0.217) and encode uniquely enriched gene pathways including ansamycin biosynthesis (DSI), tryptophan metabolism (DSII), two-component response [DSIII(b)], and the PPAR-γ signaling pathway [DSIII(a)]. Each is also associated with significantly distinct host immune responses; DSI, II, and III(b) invoked a variety of pro-inflammatory, T H 1 responses, while DSIII(a), which exhibited significantly increased incidence of nasal polyps (Fisher's exact; p = 0.034, relative risk = 2.16), primarily induced IL-5 expression (Kruskal Wallis; q = 0.045). A large proportion of CRS patient heterogeneity may be explained by the composition of their sinus bacterial microbiota and related host immune response-features which may inform strategies for tailored therapy in this patient population.

The Human Skin Microbiome Associates with the Outcome of and Is Influenced by Bacterial Infection

PubMed Central

van Rensburg, Julia J.; Lin, Huaiying; Gao, Xiang; Toh, Evelyn; Fortney, Kate R.; Ellinger, Sheila; Zwickl, Beth; Janowicz, Diane M.; Katz, Barry P.; Nelson, David E.; Dong, Qunfeng

2015-01-01

ABSTRACT The influence of the skin microbiota on host susceptibility to infectious agents is largely unexplored. The skin harbors diverse bacterial species that may promote or antagonize the growth of an invading pathogen. We developed a human infection model for Haemophilus ducreyi in which human volunteers are inoculated on the upper arm. After inoculation, papules form and either spontaneously resolve or progress to pustules. To examine the role of the skin microbiota in the outcome of H. ducreyi infection, we analyzed the microbiomes of four dose-matched pairs of “resolvers” and “pustule formers” whose inoculation sites were swabbed at multiple time points. Bacteria present on the skin were identified by amplification and pyrosequencing of 16S rRNA genes. Nonmetric multidimensional scaling (NMDS) using Bray-Curtis dissimilarity between the preinfection microbiomes of infected sites showed that sites from the same volunteer clustered together and that pustule formers segregated from resolvers (P = 0.001, permutational multivariate analysis of variance [PERMANOVA]), suggesting that the preinfection microbiomes were associated with outcome. NMDS using Bray-Curtis dissimilarity of the endpoint samples showed that the pustule sites clustered together and were significantly different than the resolved sites (P = 0.001, PERMANOVA), suggesting that the microbiomes at the endpoint differed between the two groups. In addition to H. ducreyi, pustule-forming sites had a greater abundance of Proteobacteria, Bacteroidetes, Micrococcus, Corynebacterium, Paracoccus, and Staphylococcus species, whereas resolved sites had higher levels of Actinobacteria and Propionibacterium species. These results suggest that at baseline, resolvers and pustule formers have distinct skin bacterial communities which change in response to infection and the resultant immune response. PMID:26374122

Long-Term Observations of Epibenthic Fish Zonation in the Deep Northern Gulf of Mexico

PubMed Central

Wei, Chih-Lin; Rowe, Gilbert T.; Haedrich, Richard L.; Boland, Gregory S.

2012-01-01

A total of 172 bottom trawl/skimmer samples (183 to 3655-m depth) from three deep-sea studies, R/V Alaminos cruises (1964–1973), Northern Gulf of Mexico Continental Slope (NGoMCS) study (1983–1985) and Deep Gulf of Mexico Benthos (DGoMB) program (2000 to 2002), were compiled to examine temporal and large-scale changes in epibenthic fish species composition. Based on percent species shared among samples, faunal groups (≥10% species shared) consistently reoccurred over time on the shelf-break (ca. 200 m), upper-slope (ca. 300 to 500 m) and upper-to-mid slope (ca. 500 to 1500 m) depths. These similar depth groups also merged when the three studies were pooled together, suggesting that there has been no large-scale temporal change in depth zonation on the upper section of the continental margin. Permutational multivariate analysis of variance (PERMANOVA) also detected no significant species changes on the limited sites and areas that have been revisited across the studies (P>0.05). Based on the ordination of the species shared among samples, species replacement was a continuum along a depth or macrobenthos biomass gradient. Despite the well-known, close, negative relationship between water depth and macrofaunal biomass, the fish species changed more rapidly at depth shallower than 1,000 m, but the rate of change was surprisingly slow at the highest macrofaunal biomass (>100 mg C m−2), suggesting that the composition of epibenthic fishes was not altered in response to the extremely high macrofaunal biomass in the upper Mississippi and De Soto Submarine Canyons. An alternative is that the pattern of fish species turnover is related to the decline in macrofaunal biomass, the presumptive prey of the fish, along the depth gradient. PMID:23056412

Congener Patterns of Persistent Organic Pollutants Establish the Extent of Contaminant Biotransport by Pacific Salmon in the Great Lakes.

PubMed

Gerig, Brandon S; Chaloner, Dominic T; Janetski, David J; Rediske, Richard R; O'Keefe, James P; Moerke, Ashley H; Lamberti, Gary A

2016-01-19

In the Great Lakes, introduced Pacific salmon (Oncorhynchus spp.) can transport persistent organic pollutants (POPs), such as polychlorinated biphenyls (PCBs) and polybrominated diphenyl ethers (PBDEs), to new environments during their spawning migrations. To explore the nature and extent of POP biotransport by salmon, we compared 58 PCB and 6 PBDE congeners found in spawning salmon directly to those in resident stream fish. We hypothesized that stream fish exposed to salmon spawners would have congener patterns similar to those of salmon, the presumed contaminant source. Using permutational multivariate analysis of variance (PERMANOVA) and nonmetric multidimensional scaling (NMDS), we found that POP congener patterns of Pacific salmon varied among regions in the Great Lakes basin (i.e., Lake Huron, Lake Michigan, or Lake Superior), tissue type (whole fish or eggs), and contaminant type (PCB or PBDE). For stream-resident fish, POP congener pattern was influenced by the presence of salmon, location (i.e., Great Lakes Basin), and species identity (i.e., brook trout [Salvelinus fontinalis] or mottled sculpin [Cottus bairdii]). Similarity in congener patterns indicated that salmon are a source of POPs to brook trout in stream reaches receiving salmon spawners from Lake Michigan and Lake Huron but not from Lake Superior. Congener patterns of mottled sculpin differed from those of brook trout and salmon, suggesting that brook trout and mottled sculpin either use salmon tissue to differing degrees, acquire POPs from different dietary sources, or bioaccumulate or metabolize POPs differently. Overall, our analyses identified the important role of salmon in contaminant biotransport but also demonstrated that the extent of salmon-mediated POP transfer and uptake in Great Lakes tributaries is location- and species-specific.

Voluntary and forced exercise differentially alters the gut microbiome in C57BL/6J mice.

PubMed

Allen, Jacob M; Berg Miller, Margret E; Pence, Brandt D; Whitlock, Keith; Nehra, Vandana; Gaskins, H Rex; White, Bryan A; Fryer, John D; Woods, Jeffrey A

2015-04-15

We have previously shown that voluntary wheel running (VWR) attenuates, whereas forced treadmill running (FTR) exacerbates, intestinal inflammation and clinical outcomes in a mouse model of colitis. As the gut microbiome is implicated in colitis, we hypothesized that VWR and FTR would differentially affect the gut microbiome. Mice (9-10/treatment) were randomly assigned to VWR, FTR, or sedentary home cage control (SED) for 6 wk. VWR were given running wheel access, whereas FTR ran on a treadmill for 40 min/day at 8-12 m/min, 5% grade. Forty-eight hours after the last exercise session, DNA was isolated from the fecal pellets and cecal contents, and the conserved bacterial 16S rRNA gene was amplified and sequenced using the Illumina Miseq platform. Permutational multivariate analysis of variance based on weighted UniFrac distance matrix revealed different bacterial clusters between feces and cecal contents in all groups (P < 0.01). Interestingly, the community structures of the three treatment groups clustered separately from each other in both gut regions (P < 0.05). Contrary to our hypothesis, the α-diversity metric, Chao1, indicated that VWR led to reduced bacterial richness compared with FTR or SED (P < 0.05). Taxonomic evaluation revealed that both VWR and FTR altered many individual bacterial taxa. Of particular interest, Turicibacter spp., which has been strongly associated with immune function and bowel disease, was significantly lower in VWR vs. SED/FTR. These data indicate that VWR and FTR differentially alter the intestinal microbiome of mice. These effects were observed in both the feces and cecum despite vastly different community structures between each intestinal region. Copyright © 2015 the American Physiological Society.

Maternal group B Streptococcus and the infant gut microbiota.

PubMed

Cassidy-Bushrow, A E; Sitarik, A; Levin, A M; Lynch, S V; Havstad, S; Ownby, D R; Johnson, C C; Wegienka, G

2016-02-01

Early patterns of gut colonization may predispose children to adult disease. Exposures in utero and during delivery are associated with the infant gut microbiome. Although ~35% of women carry group B strep (GBS; Streptococcus agalactiae) during pregnancy, it is unknown if GBS presence influences the infant gut microbiome. As part of a population-based, general risk birth cohort, stool specimens were collected from infant's diapers at research visits conducted at ~1 and 6 months of age. Using the Illumina MiSeq (San Diego, CA) platform, the V4 region of the bacterial 16S rRNA gene was sequenced. Infant gut bacterial community compositional differences by maternal GBS status were evaluated using permutational multivariate analysis of variance. Individual operational taxonomic units (OTUs) were tested using a zero-inflated negative binomial model. Data on maternal GBS and infant gut microbiota from either 1 (n=112) or 6-month-old stool (n=150) specimens was available on 262 maternal-child pairs. Eighty women (30.5%) were GBS+, of who 58 (72.5%) were given intrapartum antibiotics. After adjusting for maternal race, prenatal antifungal use and intrapartum antibiotics, maternal GBS status was statistically significantly associated with gut bacterial composition in the 6 month visit specimen (Canberra R 2=0.008, P=0.008; Unweighted UniFrac R 2=0.010, P=0.011). Individual OTU tests revealed that infants of GBS+ mothers were significantly enriched for specific members of the Clostridiaceae, Ruminococcoceae, and Enterococcaceae in the 6 month specimens compared with infants of GBS- mothers. Whether these taxonomic differences in infant gut microbiota at 6 months lead to differential predisposition for adult disease requires additional study.

Long-term observations of epibenthic fish zonation in the deep northern Gulf of Mexico.

PubMed

Wei, Chih-Lin; Rowe, Gilbert T; Haedrich, Richard L; Boland, Gregory S

2012-01-01

A total of 172 bottom trawl/skimmer samples (183 to 3655-m depth) from three deep-sea studies, R/V Alaminos cruises (1964-1973), Northern Gulf of Mexico Continental Slope (NGoMCS) study (1983-1985) and Deep Gulf of Mexico Benthos (DGoMB) program (2000 to 2002), were compiled to examine temporal and large-scale changes in epibenthic fish species composition. Based on percent species shared among samples, faunal groups (≥10% species shared) consistently reoccurred over time on the shelf-break (ca. 200 m), upper-slope (ca. 300 to 500 m) and upper-to-mid slope (ca. 500 to 1500 m) depths. These similar depth groups also merged when the three studies were pooled together, suggesting that there has been no large-scale temporal change in depth zonation on the upper section of the continental margin. Permutational multivariate analysis of variance (PERMANOVA) also detected no significant species changes on the limited sites and areas that have been revisited across the studies (P>0.05). Based on the ordination of the species shared among samples, species replacement was a continuum along a depth or macrobenthos biomass gradient. Despite the well-known, close, negative relationship between water depth and macrofaunal biomass, the fish species changed more rapidly at depth shallower than 1,000 m, but the rate of change was surprisingly slow at the highest macrofaunal biomass (>100 mg C m(-2)), suggesting that the composition of epibenthic fishes was not altered in response to the extremely high macrofaunal biomass in the upper Mississippi and De Soto Submarine Canyons. An alternative is that the pattern of fish species turnover is related to the decline in macrofaunal biomass, the presumptive prey of the fish, along the depth gradient.

Primate vaginal microbiomes exhibit species specificity without universal Lactobacillus dominance.

PubMed

Yildirim, Suleyman; Yeoman, Carl J; Janga, Sarath Chandra; Thomas, Susan M; Ho, Mengfei; Leigh, Steven R; White, Bryan A; Wilson, Brenda A; Stumpf, Rebecca M

2014-12-01

Bacterial communities colonizing the reproductive tracts of primates (including humans) impact the health, survival and fitness of the host, and thereby the evolution of the host species. Despite their importance, we currently have a poor understanding of primate microbiomes. The composition and structure of microbial communities vary considerably depending on the host and environmental factors. We conducted comparative analyses of the primate vaginal microbiome using pyrosequencing of the 16S rRNA genes of a phylogenetically broad range of primates to test for factors affecting the diversity of primate vaginal ecosystems. The nine primate species included: humans (Homo sapiens), yellow baboons (Papio cynocephalus), olive baboons (Papio anubis), lemurs (Propithecus diadema), howler monkeys (Alouatta pigra), red colobus (Piliocolobus rufomitratus), vervets (Chlorocebus aethiops), mangabeys (Cercocebus atys) and chimpanzees (Pan troglodytes). Our results indicated that all primates exhibited host-specific vaginal microbiota and that humans were distinct from other primates in both microbiome composition and diversity. In contrast to the gut microbiome, the vaginal microbiome showed limited congruence with host phylogeny, and neither captivity nor diet elicited substantial effects on the vaginal microbiomes of primates. Permutational multivariate analysis of variance and Wilcoxon tests revealed correlations among vaginal microbiota and host species-specific socioecological factors, particularly related to sexuality, including: female promiscuity, baculum length, gestation time, mating group size and neonatal birth weight. The proportion of unclassified taxa observed in nonhuman primate samples increased with phylogenetic distance from humans, indicative of the existence of previously unrecognized microbial taxa. These findings contribute to our understanding of host-microbe variation and coevolution, microbial biogeography, and disease risk, and have important implications for the use of animal models in studies of human sexual and reproductive diseases.

Investigation of Indoor Air Quality in Houses of Macedonia.

PubMed

Vilčeková, Silvia; Apostoloski, Ilija Zoran; Mečiarová, Ľudmila; Burdová, Eva Krídlová; Kiseľák, Jozef

2017-01-01

People who live in buildings are exposed to harmful effects of indoor air pollution for many years. Therefore, our research is aimed to investigate the indoor air quality in family houses. The measurements of indoor air temperature, relative humidity, total volatile organic compounds (TVOC), particulate matters (PM) and sound pressure level were carried out in 25 houses in several cities of the Republic of Macedonia. Mean values of indoor air temperature and relative humidity ranged from 18.9 °C to 25.6 °C and from 34.1% to 68.0%, respectively. With regard to TVOC, it can be stated that excessive occurrence was recorded. Mean values ranged from 50 μg/m³ to 2610 μg/m³. Recommended value (200 μg/m³) for human exposure to TVOC was exceeded in 32% of houses. Mean concentrations of PM 2.5 (particular matter with diameter less than 2.5 μm) and PM 10 (diameter less than 10 μm) are determined to be from 16.80 μg/m³ to 30.70 μg/m³ and from 38.30 μg/m³ to 74.60 μg/m³ individually. Mean values of sound pressure level ranged from 29.8 dB(A) to 50.6 dB(A). Dependence between characteristics of buildings (Year of construction, Year of renovation, Smoke and Heating system) and data from measurements (Temperature, Relative humidity, TVOC, PM 2.5 and PM 10 ) were analyzed using R software. Van der Waerden test shows dependence of Smoke on TVOC and PM 2.5 . Permutational multivariate analysis of variance shows the effect of interaction of Renovation and Smoke.

Investigation of Indoor Air Quality in Houses of Macedonia

PubMed Central

Vilčeková, Silvia; Apostoloski, Ilija Zoran; Mečiarová, Ľudmila; Krídlová Burdová, Eva; Kiseľák, Jozef

2017-01-01

People who live in buildings are exposed to harmful effects of indoor air pollution for many years. Therefore, our research is aimed to investigate the indoor air quality in family houses. The measurements of indoor air temperature, relative humidity, total volatile organic compounds (TVOC), particulate matters (PM) and sound pressure level were carried out in 25 houses in several cities of the Republic of Macedonia. Mean values of indoor air temperature and relative humidity ranged from 18.9 °C to 25.6 °C and from 34.1% to 68.0%, respectively. With regard to TVOC, it can be stated that excessive occurrence was recorded. Mean values ranged from 50 μg/m3 to 2610 μg/m3. Recommended value (200 μg/m3) for human exposure to TVOC was exceeded in 32% of houses. Mean concentrations of PM2.5 (particular matter with diameter less than 2.5 µm) and PM10 (diameter less than 10 µm) are determined to be from 16.80 µg/m3 to 30.70 µg/m3 and from 38.30 µg/m3 to 74.60 µg/m3 individually. Mean values of sound pressure level ranged from 29.8 dB(A) to 50.6 dB(A). Dependence between characteristics of buildings (Year of construction, Year of renovation, Smoke and Heating system) and data from measurements (Temperature, Relative humidity, TVOC, PM2.5 and PM10) were analyzed using R software. Van der Waerden test shows dependence of Smoke on TVOC and PM2.5. Permutational multivariate analysis of variance shows the effect of interaction of Renovation and Smoke. PMID:28045447

Epiphytic invertebrate patterns in coastal lakes along a gradient of salinity and water exchange with the sea

NASA Astrophysics Data System (ADS)

Obolewski, Krystian; Bąkowska, Martyna

2017-10-01

The species composition and abundance of epiphytic fauna inhabiting common reed (Phragmites australis (Cav.) Trin. ex Steud.) was performed in five coastal lakes in Słowiński National Park (southern Baltic coast in northern Poland). The lakes represent a salinity gradient (from freshwater to β-oligohaline waters) and four types of coastal lakes: (1) lagoon, L (Lake Łebsko, seawater enters it permanently); (2) coastal lake with periodically brackish water, CLB (Lake Gardno); (3) freshwater costal lake, CLF (Lake Smołdzińskie); and (4) coastal dune lakes, CLD (Dołgie Wielkie and Dołgie Małe). Using statistical ordination techniques, we found that the structure of epiphytic fauna (microinvertebrates and macroinvertebrates) is determined primarily by hydrological connectivity (water exchange) with the sea. Canonical Correspondence Analysis, coupled with variance partitioning, showed that hydrological connectivity accounted for 24% of the variation in the invertebrate community, followed by physico-chemical (19%) and trophic (8%) factors. Our results indicate that the assemblages of Ciliata-libera and Cnidaria are characteristic for L (β-oligohaline), Rotifera, Suctoria, Chaetogaster sp., Gastropoda and Trichoptera are characteristic for CLB (limnetic/β-oligohaline), but no taxonomic groups are characteristic for CLF and CLD (both limnetic). The index of multivariate dispersion showed a decreasing trend with the increasing lake isolation from the open sea, except for CLD. However, in terms of the structure of epiphytic fauna, Multi-Response Permutation Procedures showed that CLD significantly differed only from CLB. Our results suggest that the identified characteristic taxonomic groups of plant-associated macroinvertebrates have a high potential to be used as bioindicators of salinity and water exchange with the sea, due to their sensitivity to environmental stress.

Hemorrhagic Complications of Percutaneous Cryoablation for Renal Tumors: Results from a 7-year Prospective Study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kakarala, Bharat, E-mail: bkakara1@jhmi.edu, E-mail: bharat.kakarala@gmail.com; Frangakis, Constantine E., E-mail: cfrangak@jhsph.edu; Rodriguez, Ron, E-mail: rodriguezr32@uthscsa.edu

PurposeCryoablation of renal tumors is assumed to have a higher risk of hemorrhagic complications compared to other ablative modalities. Our purpose was to establish the exact risk and to identify hemorrhagic risk factors.Materials and MethodsThis IRB approved, 7-year prospective study included 261 renal cryoablations. Procedures were under conscious sedation and CT guidance. Pre- and postablation CT was obtained, and hemorrhagic complications were CTCAE tabulated. Age, gender, tumor size, histology, and probes number were tested based on averages or proportions using their exact permutation distribution. “High-risk” subgroups (those exceeding the thresholds of all variables) were tested for each variable alone, andmore » for all combinations of variable threshold values. We compared the subgroup with the best PPV using one variable, with the subgroup with the best PPV using all variables (McNemmar test).ResultsThe hemorrhagic complication rate was 3.5 %. Four patients required transfusions, two required emergent angiograms, one required both a transfusion and angiogram, and two required bladder irrigation for outlet obstruction. Perirenal space hemorrhage was more clinically significant than elsewhere. Univariate risks were tumor size >2 cm, number of probes >2, and malignant histology (P = 0.005, 0.002, and 0.033, respectively). Multivariate analysis showed that patients >55 years with malignant tumors >2 cm requiring 2 or more probes yielded the highest PPV (7.5 %).ConclusionsAlthough older patients (>55 years old) with larger (>2 cm), malignant tumors have an increased risk of hemorrhagic complications, the low PPV does not support the routine use of embolization. Percutaneous cryoablation has a 3.5 % risk of significant hemorrhage, similar to that reported for other types of renal ablative modalities.« less

Serum protein profiling using an aptamer array predicts clinical outcomes of stage IIA colon cancer: A leave-one-out crossvalidation

PubMed Central

Huh, Jung Wook; Kim, Sung Chun; Sohn, Insuk; Jung, Sin-Ho; Kim, Hee Cheol

2016-01-01

Background In this study, we established and validated a model for predicting prognosis of stage IIA colon cancer patients based on expression profiles of aptamers in serum. Methods Bloods samples were collected from 227 consecutive patients with pathologic T3N0M0 (stage IIA) colon cancer. We incubated 1,149 serum molecule-binding aptamer pools of clinical significance with serum from patients to obtain aptamers bound to serum molecules, which were then amplified and marked. Oligonucleotide arrays were constructed with the base sequences of the 1,149 aptamers, and the marked products identified above were reacted with one another to produce profiles of the aptamers bound to serum molecules. These profiles were organized into low- and high-risk groups of colon cancer patients based on clinical information for the serum samples. Cox proportional hazards model and leave-one-out cross-validation (LOOCV) were used to evaluate predictive performance. Results During a median follow-up period of 5 years, 29 of the 227 patients (11.9%) experienced recurrence. There were 212 patients (93.4%) in the low-risk group and 15 patients (6.6%) in the high-risk group in our aptamer prognosis model. Postoperative recurrence significantly correlated with age and aptamer risk stratification (p = 0.046 and p = 0.001, respectively). In multivariate analysis, aptamer risk stratification (p < 0.001) was an independent predictor of recurrence. Disease-free survival curves calculated according to aptamer risk level predicted through a LOOCV procedure and age showed significant differences (p < 0.001 from permutations). Conclusion Aptamer risk stratification can be a valuable prognostic factor in stage II colon cancer patients. PMID:26908450

PROMISE: a tool to identify genomic features with a specific biologically interesting pattern of associations with multiple endpoint variables

PubMed Central

Pounds, Stan; Cheng, Cheng; Cao, Xueyuan; Crews, Kristine R.; Plunkett, William; Gandhi, Varsha; Rubnitz, Jeffrey; Ribeiro, Raul C.; Downing, James R.; Lamba, Jatinder

2009-01-01

Motivation: In some applications, prior biological knowledge can be used to define a specific pattern of association of multiple endpoint variables with a genomic variable that is biologically most interesting. However, to our knowledge, there is no statistical procedure designed to detect specific patterns of association with multiple endpoint variables. Results: Projection onto the most interesting statistical evidence (PROMISE) is proposed as a general procedure to identify genomic variables that exhibit a specific biologically interesting pattern of association with multiple endpoint variables. Biological knowledge of the endpoint variables is used to define a vector that represents the biologically most interesting values for statistics that characterize the associations of the endpoint variables with a genomic variable. A test statistic is defined as the dot-product of the vector of the observed association statistics and the vector of the most interesting values of the association statistics. By definition, this test statistic is proportional to the length of the projection of the observed vector of correlations onto the vector of most interesting associations. Statistical significance is determined via permutation. In simulation studies and an example application, PROMISE shows greater statistical power to identify genes with the interesting pattern of associations than classical multivariate procedures, individual endpoint analyses or listing genes that have the pattern of interest and are significant in more than one individual endpoint analysis. Availability: Documented R routines are freely available from www.stjuderesearch.org/depts/biostats and will soon be available as a Bioconductor package from www.bioconductor.org. Contact: stanley.pounds@stjude.org Supplementary information: Supplementary data are available at Bioinformatics online. PMID:19528086

Deconstructing multivariate decoding for the study of brain function.

PubMed

Hebart, Martin N; Baker, Chris I

2017-08-04

Multivariate decoding methods were developed originally as tools to enable accurate predictions in real-world applications. The realization that these methods can also be employed to study brain function has led to their widespread adoption in the neurosciences. However, prior to the rise of multivariate decoding, the study of brain function was firmly embedded in a statistical philosophy grounded on univariate methods of data analysis. In this way, multivariate decoding for brain interpretation grew out of two established frameworks: multivariate decoding for predictions in real-world applications, and classical univariate analysis based on the study and interpretation of brain activation. We argue that this led to two confusions, one reflecting a mixture of multivariate decoding for prediction or interpretation, and the other a mixture of the conceptual and statistical philosophies underlying multivariate decoding and classical univariate analysis. Here we attempt to systematically disambiguate multivariate decoding for the study of brain function from the frameworks it grew out of. After elaborating these confusions and their consequences, we describe six, often unappreciated, differences between classical univariate analysis and multivariate decoding. We then focus on how the common interpretation of what is signal and noise changes in multivariate decoding. Finally, we use four examples to illustrate where these confusions may impact the interpretation of neuroimaging data. We conclude with a discussion of potential strategies to help resolve these confusions in interpreting multivariate decoding results, including the potential departure from multivariate decoding methods for the study of brain function. Copyright © 2017. Published by Elsevier Inc.

Multivariate meta-analysis: Potential and promise

PubMed Central

Jackson, Dan; Riley, Richard; White, Ian R

2011-01-01

The multivariate random effects model is a generalization of the standard univariate model. Multivariate meta-analysis is becoming more commonly used and the techniques and related computer software, although continually under development, are now in place. In order to raise awareness of the multivariate methods, and discuss their advantages and disadvantages, we organized a one day ‘Multivariate meta-analysis’ event at the Royal Statistical Society. In addition to disseminating the most recent developments, we also received an abundance of comments, concerns, insights, critiques and encouragement. This article provides a balanced account of the day's discourse. By giving others the opportunity to respond to our assessment, we hope to ensure that the various view points and opinions are aired before multivariate meta-analysis simply becomes another widely used de facto method without any proper consideration of it by the medical statistics community. We describe the areas of application that multivariate meta-analysis has found, the methods available, the difficulties typically encountered and the arguments for and against the multivariate methods, using four representative but contrasting examples. We conclude that the multivariate methods can be useful, and in particular can provide estimates with better statistical properties, but also that these benefits come at the price of making more assumptions which do not result in better inference in every case. Although there is evidence that multivariate meta-analysis has considerable potential, it must be even more carefully applied than its univariate counterpart in practice. Copyright © 2011 John Wiley & Sons, Ltd. PMID:21268052

Permuting input for more effective sampling of 3D conformer space

NASA Astrophysics Data System (ADS)

Carta, Giorgio; Onnis, Valeria; Knox, Andrew J. S.; Fayne, Darren; Lloyd, David G.

2006-03-01

SMILES strings and other classic 2D structural formats offer a convenient way to represent molecules as a simplistic connection table, with the inherent advantages of ease of handling and storage. In the context of virtual screening, chemical databases to be screened are often initially represented by canonicalised SMILES strings that can be filtered and pre-processed in a number of ways, resulting in molecules that occupy similar regions of chemical space to active compounds of a therapeutic target. A wide variety of software exists to convert molecules into SMILES format, namely, Mol2smi (Daylight Inc.), MOE (Chemical Computing Group) and Babel (Openeye Scientific Software). Depending on the algorithm employed, the atoms of a SMILES string defining a molecule can be ordered differently. Upon conversion to 3D coordinates they result in the production of ostensibly the same molecule. In this work we show how different permutations of a SMILES string can affect conformer generation, affecting reliability and repeatability of the results. Furthermore, we propose a novel procedure for the generation of conformers, taking advantage of the permutation of the input strings—both SMILES and other 2D formats, leading to more effective sampling of conformation space in output, and also implementing fingerprint and principal component analyses step to post process and visualise the results.

Estimating Temporal Causal Interaction between Spike Trains with Permutation and Transfer Entropy

PubMed Central

Li, Zhaohui; Li, Xiaoli

2013-01-01

Estimating the causal interaction between neurons is very important for better understanding the functional connectivity in neuronal networks. We propose a method called normalized permutation transfer entropy (NPTE) to evaluate the temporal causal interaction between spike trains, which quantifies the fraction of ordinal information in a neuron that has presented in another one. The performance of this method is evaluated with the spike trains generated by an Izhikevich’s neuronal model. Results show that the NPTE method can effectively estimate the causal interaction between two neurons without influence of data length. Considering both the precision of time delay estimated and the robustness of information flow estimated against neuronal firing rate, the NPTE method is superior to other information theoretic method including normalized transfer entropy, symbolic transfer entropy and permutation conditional mutual information. To test the performance of NPTE on analyzing simulated biophysically realistic synapses, an Izhikevich’s cortical network that based on the neuronal model is employed. It is found that the NPTE method is able to characterize mutual interactions and identify spurious causality in a network of three neurons exactly. We conclude that the proposed method can obtain more reliable comparison of interactions between different pairs of neurons and is a promising tool to uncover more details on the neural coding. PMID:23940662

Unequal homologous recombination between tandemly arranged sequences stably incorporated into cultured rat cells.

PubMed Central

Stringer, J R; Kuhn, R M; Newman, J L; Meade, J C

1985-01-01

Cultured rat cells deficient in endogenous thymidine kinase activity (tk) were stably transformed with a recombination-indicator DNA substrate constructed in vitro by rearrangement of the herpes simplex virus tk gene sequences into a partially redundant permutation of the functional gene. The recombination-indicator DNA did not express tk, but was designed to allow formation of a functional tk gene via homologous recombination. A clonal cell line (519) was isolated that harbored several permuted herpes simplex virus tk genes. 519 cells spontaneously produced progeny that survived in medium containing hypoxanthine, aminopterin, and thymidine. Acquisition of resistance to hypoxanthine, aminopterin, and thymidine was accompanied by the rearrangement of the defective tk gene to functional configuration. The rearrangement apparently occurred by unequal exchange between one permuted tk gene and a replicated copy of itself. Recombination was between 500-base-pair tracts of DNA sequence homology that were separated by 3.4 kilobases. Exchanges occurred spontaneously at a frequency of approximately 5 X 10(-6) events per cell per generation. Recombination also mediated reversion to the tk- phenotype; however, the predominant mechanism by which cells escaped death in the presence of drugs rendered toxic by thymidine kinase was not recombination, but rather inactivation of the intact tk gene. Images PMID:3016511

Detecting the influence of rare stressors on rare species in Yosemite National Park using a novel stratified permutation test

USGS Publications Warehouse

Matchett, John R.; Stark, Philip B.; Ostoja, Steven M.; Knapp, Roland A.; McKenny, Heather C.; Brooks, Matthew L.; Langford, William T.; Joppa, Lucas N.; Berlow, Eric L.

2015-01-01

Statistical models often use observational data to predict phenomena; however, interpreting model terms to understand their influence can be problematic. This issue poses a challenge in species conservation where setting priorities requires estimating influences of potential stressors using observational data. We present a novel approach for inferring influence of a rare stressor on a rare species by blending predictive models with nonparametric permutation tests. We illustrate the approach with two case studies involving rare amphibians in Yosemite National Park, USA. The endangered frog, Rana sierrae, is known to be negatively impacted by non-native fish, while the threatened toad, Anaxyrus canorus, is potentially affected by packstock. Both stressors and amphibians are rare, occurring in ~10% of potential habitat patches. We first predict amphibian occupancy with a statistical model that includes all predictors but the stressor to stratify potential habitat by predicted suitability. A stratified permutation test then evaluates the association between stressor and amphibian, all else equal. Our approach confirms the known negative relationship between fish and R. sierrae, but finds no evidence of a negative relationship between current packstock use and A. canorus breeding. Our statistical approach has potential broad application for deriving understanding (not just prediction) from observational data.

A Space–Time Permutation Scan Statistic for Disease Outbreak Detection

PubMed Central

Kulldorff, Martin; Heffernan, Richard; Hartman, Jessica; Assunção, Renato; Mostashari, Farzad

2005-01-01

Background The ability to detect disease outbreaks early is important in order to minimize morbidity and mortality through timely implementation of disease prevention and control measures. Many national, state, and local health departments are launching disease surveillance systems with daily analyses of hospital emergency department visits, ambulance dispatch calls, or pharmacy sales for which population-at-risk information is unavailable or irrelevant. Methods and Findings We propose a prospective space–time permutation scan statistic for the early detection of disease outbreaks that uses only case numbers, with no need for population-at-risk data. It makes minimal assumptions about the time, geographical location, or size of the outbreak, and it adjusts for natural purely spatial and purely temporal variation. The new method was evaluated using daily analyses of hospital emergency department visits in New York City. Four of the five strongest signals were likely local precursors to citywide outbreaks due to rotavirus, norovirus, and influenza. The number of false signals was at most modest. Conclusion If such results hold up over longer study times and in other locations, the space–time permutation scan statistic will be an important tool for local and national health departments that are setting up early disease detection surveillance systems. PMID:15719066

Detecting the influence of rare stressors on rare species in Yosemite National Park using a novel stratified permutation test

PubMed Central

Matchett, J. R.; Stark, Philip B.; Ostoja, Steven M.; Knapp, Roland A.; McKenny, Heather C.; Brooks, Matthew L.; Langford, William T.; Joppa, Lucas N.; Berlow, Eric L.

2015-01-01

Statistical models often use observational data to predict phenomena; however, interpreting model terms to understand their influence can be problematic. This issue poses a challenge in species conservation where setting priorities requires estimating influences of potential stressors using observational data. We present a novel approach for inferring influence of a rare stressor on a rare species by blending predictive models with nonparametric permutation tests. We illustrate the approach with two case studies involving rare amphibians in Yosemite National Park, USA. The endangered frog, Rana sierrae, is known to be negatively impacted by non-native fish, while the threatened toad, Anaxyrus canorus, is potentially affected by packstock. Both stressors and amphibians are rare, occurring in ~10% of potential habitat patches. We first predict amphibian occupancy with a statistical model that includes all predictors but the stressor to stratify potential habitat by predicted suitability. A stratified permutation test then evaluates the association between stressor and amphibian, all else equal. Our approach confirms the known negative relationship between fish and R. sierrae, but finds no evidence of a negative relationship between current packstock use and A. canorus breeding. Our statistical approach has potential broad application for deriving understanding (not just prediction) from observational data. PMID:26031755

Limited Rationality and Its Quantification Through the Interval Number Judgments With Permutations.

PubMed

Liu, Fang; Pedrycz, Witold; Zhang, Wei-Guo

2017-12-01

The relative importance of alternatives expressed in terms of interval numbers in the fuzzy analytic hierarchy process aims to capture the uncertainty experienced by decision makers (DMs) when making a series of comparisons. Under the assumption of full rationality, the judgements of DMs in the typical analytic hierarchy process could be consistent. However, since the uncertainty in articulating the opinions of DMs is unavoidable, the interval number judgements are associated with the limited rationality. In this paper, we investigate the concept of limited rationality by introducing interval multiplicative reciprocal comparison matrices. By analyzing the consistency of interval multiplicative reciprocal comparison matrices, it is observed that the interval number judgements are inconsistent. By considering the permutations of alternatives, the concepts of approximation-consistency and acceptable approximation-consistency of interval multiplicative reciprocal comparison matrices are proposed. The exchange method is designed to generate all the permutations. A novel method of determining the interval weight vector is proposed under the consideration of randomness in comparing alternatives, and a vector of interval weights is determined. A new algorithm of solving decision making problems with interval multiplicative reciprocal preference relations is provided. Two numerical examples are carried out to illustrate the proposed approach and offer a comparison with the methods available in the literature.

Tensor models, Kronecker coefficients and permutation centralizer algebras

NASA Astrophysics Data System (ADS)

Geloun, Joseph Ben; Ramgoolam, Sanjaye

2017-11-01

We show that the counting of observables and correlators for a 3-index tensor model are organized by the structure of a family of permutation centralizer algebras. These algebras are shown to be semi-simple and their Wedderburn-Artin decompositions into matrix blocks are given in terms of Clebsch-Gordan coefficients of symmetric groups. The matrix basis for the algebras also gives an orthogonal basis for the tensor observables which diagonalizes the Gaussian two-point functions. The centres of the algebras are associated with correlators which are expressible in terms of Kronecker coefficients (Clebsch-Gordan multiplicities of symmetric groups). The color-exchange symmetry present in the Gaussian model, as well as a large class of interacting models, is used to refine the description of the permutation centralizer algebras. This discussion is extended to a general number of colors d: it is used to prove the integrality of an infinite family of number sequences related to color-symmetrizations of colored graphs, and expressible in terms of symmetric group representation theory data. Generalizing a connection between matrix models and Belyi maps, correlators in Gaussian tensor models are interpreted in terms of covers of singular 2-complexes. There is an intriguing difference, between matrix and higher rank tensor models, in the computational complexity of superficially comparable correlators of observables parametrized by Young diagrams.

Refined composite multiscale weighted-permutation entropy of financial time series

NASA Astrophysics Data System (ADS)

Zhang, Yongping; Shang, Pengjian

2018-04-01

For quantifying the complexity of nonlinear systems, multiscale weighted-permutation entropy (MWPE) has recently been proposed. MWPE has incorporated amplitude information and been applied to account for the multiple inherent dynamics of time series. However, MWPE may be unreliable, because its estimated values show large fluctuation for slight variation of the data locations, and a significant distinction only for the different length of time series. Therefore, we propose the refined composite multiscale weighted-permutation entropy (RCMWPE). By comparing the RCMWPE results with other methods' results on both synthetic data and financial time series, RCMWPE method shows not only the advantages inherited from MWPE but also lower sensitivity to the data locations, more stable and much less dependent on the length of time series. Moreover, we present and discuss the results of RCMWPE method on the daily price return series from Asian and European stock markets. There are significant differences between Asian markets and European markets, and the entropy values of Hang Seng Index (HSI) are close to but higher than those of European markets. The reliability of the proposed RCMWPE method has been supported by simulations on generated and real data. It could be applied to a variety of fields to quantify the complexity of the systems over multiple scales more accurately.

FieldTrip: Open Source Software for Advanced Analysis of MEG, EEG, and Invasive Electrophysiological Data

PubMed Central

Oostenveld, Robert; Fries, Pascal; Maris, Eric; Schoffelen, Jan-Mathijs

2011-01-01

This paper describes FieldTrip, an open source software package that we developed for the analysis of MEG, EEG, and other electrophysiological data. The software is implemented as a MATLAB toolbox and includes a complete set of consistent and user-friendly high-level functions that allow experimental neuroscientists to analyze experimental data. It includes algorithms for simple and advanced analysis, such as time-frequency analysis using multitapers, source reconstruction using dipoles, distributed sources and beamformers, connectivity analysis, and nonparametric statistical permutation tests at the channel and source level. The implementation as toolbox allows the user to perform elaborate and structured analyses of large data sets using the MATLAB command line and batch scripting. Furthermore, users and developers can easily extend the functionality and implement new algorithms. The modular design facilitates the reuse in other software packages. PMID:21253357

Multivariate Longitudinal Analysis with Bivariate Correlation Test

PubMed Central

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model’s parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated. PMID:27537692

Multivariate Longitudinal Analysis with Bivariate Correlation Test.

PubMed

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model's parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated.

Deciphering the Preference and Predicting the Viability of Circular Permutations in Proteins

PubMed Central

Liu, Yen-Yi; Wang, Li-Fen; Hwang, Jenn-Kang; Lyu, Ping-Chiang

2012-01-01

Circular permutation (CP) refers to situations in which the termini of a protein are relocated to other positions in the structure. CP occurs naturally and has been artificially created to study protein function, stability and folding. Recently CP is increasingly applied to engineer enzyme structure and function, and to create bifunctional fusion proteins unachievable by tandem fusion. CP is a complicated and expensive technique. An intrinsic difficulty in its application lies in the fact that not every position in a protein is amenable for creating a viable permutant. To examine the preferences of CP and develop CP viability prediction methods, we carried out comprehensive analyses of the sequence, structural, and dynamical properties of known CP sites using a variety of statistics and simulation methods, such as the bootstrap aggregating, permutation test and molecular dynamics simulations. CP particularly favors Gly, Pro, Asp and Asn. Positions preferred by CP lie within coils, loops, turns, and at residues that are exposed to solvent, weakly hydrogen-bonded, environmentally unpacked, or flexible. Disfavored positions include Cys, bulky hydrophobic residues, and residues located within helices or near the protein's core. These results fostered the development of an effective viable CP site prediction system, which combined four machine learning methods, e.g., artificial neural networks, the support vector machine, a random forest, and a hierarchical feature integration procedure developed in this work. As assessed by using the hydrofolate reductase dataset as the independent evaluation dataset, this prediction system achieved an AUC of 0.9. Large-scale predictions have been performed for nine thousand representative protein structures; several new potential applications of CP were thus identified. Many unreported preferences of CP are revealed in this study. The developed system is the best CP viability prediction method currently available. This work will facilitate the application of CP in research and biotechnology. PMID:22359629

Assessing Discriminative Performance at External Validation of Clinical Prediction Models

PubMed Central

Nieboer, Daan; van der Ploeg, Tjeerd; Steyerberg, Ewout W.

2016-01-01

Introduction External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. Methods We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. Results The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. Conclusion The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients. PMID:26881753

On the rank-distance median of 3 permutations.

PubMed

Chindelevitch, Leonid; Pereira Zanetti, João Paulo; Meidanis, João

2018-05-08

Recently, Pereira Zanetti, Biller and Meidanis have proposed a new definition of a rearrangement distance between genomes. In this formulation, each genome is represented as a matrix, and the distance d is the rank distance between these matrices. Although defined in terms of matrices, the rank distance is equal to the minimum total weight of a series of weighted operations that leads from one genome to the other, including inversions, translocations, transpositions, and others. The computational complexity of the median-of-three problem according to this distance is currently unknown. The genome matrices are a special kind of permutation matrices, which we study in this paper. In their paper, the authors provide an [Formula: see text] algorithm for determining three candidate medians, prove the tight approximation ratio [Formula: see text], and provide a sufficient condition for their candidates to be true medians. They also conduct some experiments that suggest that their method is accurate on simulated and real data. In this paper, we extend their results and provide the following: Three invariants characterizing the problem of finding the median of 3 matrices A sufficient condition for uniqueness of medians that can be checked in O(n) A faster, [Formula: see text] algorithm for determining the median under this condition A new heuristic algorithm for this problem based on compressed sensing A [Formula: see text] algorithm that exactly solves the problem when the inputs are orthogonal matrices, a class that includes both permutations and genomes as special cases. Our work provides the first proof that, with respect to the rank distance, the problem of finding the median of 3 genomes, as well as the median of 3 permutations, is exactly solvable in polynomial time, a result which should be contrasted with its NP-hardness for the DCJ (double cut-and-join) distance and most other families of genome rearrangement operations. This result, backed by our experimental tests, indicates that the rank distance is a viable alternative to the DCJ distance widely used in genome comparisons.

Identification of IL-7 as a candidate disease mediator in osteoarthritis in Chinese Han population: a case-control study.

PubMed

Zhang, Hong-Xin; Wang, Yan-Gui; Lu, Shun-Yuan; Lu, Xiong-Xiong; Liu, Jie

2016-09-01

Little is known about the biochemical mediators IL-7 that correlate with the initiation and progression of OA. We performed this study to assess the role of variants of IL-7 in OA susceptibility in the Chinese Han population. We performed a retrospective, case-control study in the Chinese Han population from 2013 to 2015. Four single nucleotide polymorphisms were genotyped (using a ligase detection reaction) in 602 patients and 454 controls. Differences between groups were analysed, and association was assessed by the odds ratio (OR) and 95% CI. Among these polymorphisms, rs2583764, rs2583760 and rs6993386 showed no significant association with OA in the Chinese Han population {rs2583764 [P-allele = 0.98651, P-genotype = 0.40392, OR (95% CI): 1.00162 (0.83066, 1.20775)]; rs2583760 [P-allele = 0.384500, P-genotype = 0.58752, OR (95% CI): 0.69859 (0.30996, 1.57449)]; rs6993386 [P-allele = 0.69525, P-genotype = 0.50712, OR (95% CI): 0.96432 (0.80406, 1.15653)]}. However, the results showed that the rs2583759 polymorphism was significantly associated with OA [P-allele = 0.00 P-genotype = 3.86 × 10(-30), OR (95% CI): 0.27794 (0.22407, 0.34476)], even when the 10 000 times permutation was performed (P-allele-permutation < 0.00010, P-genotype-permutation = 0.00010). Haplotype analyses showed A-G-A-C, A-G-A-T and G-G-G-C of rs2583764-rs2583760-rs6993386-rs2583759 were risk factors for OA, both before or after the 10 000 times permutation, indicating IL-7 to be associated with OA. There was a significant association between IL-7, especially rs2583759, and OA in the Chinese Han population. © The Author 2016. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Assessing Discriminative Performance at External Validation of Clinical Prediction Models.

PubMed

Nieboer, Daan; van der Ploeg, Tjeerd; Steyerberg, Ewout W

2016-01-01

External validation studies are essential to study the generalizability of prediction models. Recently a permutation test, focusing on discrimination as quantified by the c-statistic, was proposed to judge whether a prediction model is transportable to a new setting. We aimed to evaluate this test and compare it to previously proposed procedures to judge any changes in c-statistic from development to external validation setting. We compared the use of the permutation test to the use of benchmark values of the c-statistic following from a previously proposed framework to judge transportability of a prediction model. In a simulation study we developed a prediction model with logistic regression on a development set and validated them in the validation set. We concentrated on two scenarios: 1) the case-mix was more heterogeneous and predictor effects were weaker in the validation set compared to the development set, and 2) the case-mix was less heterogeneous in the validation set and predictor effects were identical in the validation and development set. Furthermore we illustrated the methods in a case study using 15 datasets of patients suffering from traumatic brain injury. The permutation test indicated that the validation and development set were homogenous in scenario 1 (in almost all simulated samples) and heterogeneous in scenario 2 (in 17%-39% of simulated samples). Previously proposed benchmark values of the c-statistic and the standard deviation of the linear predictors correctly pointed at the more heterogeneous case-mix in scenario 1 and the less heterogeneous case-mix in scenario 2. The recently proposed permutation test may provide misleading results when externally validating prediction models in the presence of case-mix differences between the development and validation population. To correctly interpret the c-statistic found at external validation it is crucial to disentangle case-mix differences from incorrect regression coefficients.

Genuine multipartite entanglement of symmetric Gaussian states: Strong monogamy, unitary localization, scaling behavior, and molecular sharing structure

NASA Astrophysics Data System (ADS)

Adesso, Gerardo; Illuminati, Fabrizio

2008-10-01

We investigate the structural aspects of genuine multipartite entanglement in Gaussian states of continuous variable systems. Generalizing the results of Adesso and Illuminati [Phys. Rev. Lett. 99, 150501 (2007)], we analyze whether the entanglement shared by blocks of modes distributes according to a strong monogamy law. This property, once established, allows us to quantify the genuine N -partite entanglement not encoded into 2,…,K,…,(N-1) -partite quantum correlations. Strong monogamy is numerically verified, and the explicit expression of the measure of residual genuine multipartite entanglement is analytically derived, by a recursive formula, for a subclass of Gaussian states. These are fully symmetric (permutation-invariant) states that are multipartitioned into blocks, each consisting of an arbitrarily assigned number of modes. We compute the genuine multipartite entanglement shared by the blocks of modes and investigate its scaling properties with the number and size of the blocks, the total number of modes, the global mixedness of the state, and the squeezed resources needed for state engineering. To achieve the exact computation of the block entanglement, we introduce and prove a general result of symplectic analysis: Correlations among K blocks in N -mode multisymmetric and multipartite Gaussian states, which are locally invariant under permutation of modes within each block, can be transformed by a local (with respect to the partition) unitary operation into correlations shared by K single modes, one per block, in effective nonsymmetric states where N-K modes are completely uncorrelated. Due to this theorem, the above results, such as the derivation of the explicit expression for the residual multipartite entanglement, its nonnegativity, and its scaling properties, extend to the subclass of non-symmetric Gaussian states that are obtained by the unitary localization of the multipartite entanglement of symmetric states. These findings provide strong numerical evidence that the distributed Gaussian entanglement is strongly monogamous under and possibly beyond specific symmetry constraints, and that the residual continuous-variable tangle is a proper measure of genuine multipartite entanglement for permutation-invariant Gaussian states under any multipartition of the modes.

Multivariate Regression Analysis and Slaughter Livestock,

DTIC Science & Technology

AGRICULTURE, *ECONOMICS), (*MEAT, PRODUCTION), MULTIVARIATE ANALYSIS, REGRESSION ANALYSIS , ANIMALS, WEIGHT, COSTS, PREDICTIONS, STABILITY, MATHEMATICAL MODELS, STORAGE, BEEF, PORK, FOOD, STATISTICAL DATA, ACCURACY

Possible signatures of dissipation from time-series analysis techniques using a turbulent laboratory magnetohydrodynamic plasma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schaffner, D. A.; Brown, M. R.; Rock, A. B.

The frequency spectrum of magnetic fluctuations as measured on the Swarthmore Spheromak Experiment is broadband and exhibits a nearly Kolmogorov 5/3 scaling. It features a steepening region which is indicative of dissipation of magnetic fluctuation energy similar to that observed in fluid and magnetohydrodynamic turbulence systems. Two non-spectrum based time-series analysis techniques are implemented on this data set in order to seek other possible signatures of turbulent dissipation beyond just the steepening of fluctuation spectra. Presented here are results for the flatness, permutation entropy, and statistical complexity, each of which exhibits a particular character at spectral steepening scales which canmore » then be compared to the behavior of the frequency spectrum.« less

Spectral analysis of time series of categorical variables in earth sciences

NASA Astrophysics Data System (ADS)

Pardo-Igúzquiza, Eulogio; Rodríguez-Tovar, Francisco J.; Dorador, Javier

2016-10-01

Time series of categorical variables often appear in Earth Science disciplines and there is considerable interest in studying their cyclic behavior. This is true, for example, when the type of facies, petrofabric features, ichnofabrics, fossil assemblages or mineral compositions are measured continuously over a core or throughout a stratigraphic succession. Here we deal with the problem of applying spectral analysis to such sequences. A full indicator approach is proposed to complement the spectral envelope often used in other disciplines. Additionally, a stand-alone computer program is provided for calculating the spectral envelope, in this case implementing the permutation test to assess the statistical significance of the spectral peaks. We studied simulated sequences as well as real data in order to illustrate the methodology.

Variation in the shape and mechanical performance of the lower jaws in ceratopsid dinosaurs (Ornithischia, Ceratopsia).

PubMed

Maiorino, Leonardo; Farke, Andrew A; Kotsakis, Tassos; Teresi, Luciano; Piras, Paolo

2015-11-01

Ceratopsidae represents a group of quadrupedal herbivorous dinosaurs that inhabited western North America and eastern Asia during the Late Cretaceous. Although horns and frills of the cranium are highly variable across species, the lower jaw historically has been considered to be relatively conservative in morphology. Here, the lower jaws from 58 specimens representing 21 ceratopsoid taxa were sampled, using geometric morphometrics and 2D finite element analysis (FEA) to explore differences in morphology and mechanical performance across Ceratopsoidea (the clade including Ceratopsidae, Turanoceratops and Zuniceratops). Principal component analyses and non-parametric permuted manovas highlight Triceratopsini as a morphologically distinct clade within the sample. A relatively robust and elongate dentary, a larger and more elongated coronoid process, and a small and dorso-ventrally compressed angular characterize this clade, as well as the absolutely larger size. By contrast, non-triceratopsin chasmosaurines, Centrosaurini and Pachyrhinosaurini have similar morphologies to each other. Zuniceratops and Avaceratops are distinct from other taxa. No differences in size between Pachyrhinosaurini and Centrosaurini are recovered using non-parametric permuted anovas. Structural performance, as evaluated using a 2D FEA, is similar across all groups as measured by overall stress, with the exception of Triceratopsini. Shape, size and stress are phylogenetically constrained. A longer dentary as well as a long coronoid process result in a lower jaw that is reconstructed as relatively much more stressed in triceratopsins. © 2015 Anatomical Society.

The role of ADP-ribosylation in regulating DNA interstrand crosslink repair

PubMed Central

Gunn, Alasdair R.; Banos-Pinero, Benito; Paschke, Peggy; Sanchez-Pulido, Luis; Ariza, Antonio; Day, Joseph; Emrich, Mehera; Leys, David; Ponting, Chris P.

2016-01-01

ABSTRACT ADP-ribosylation by ADP-ribosyltransferases (ARTs) has a well-established role in DNA strand break repair by promoting enrichment of repair factors at damage sites through ADP-ribose interaction domains. Here, we exploit the simple eukaryote Dictyostelium to uncover a role for ADP-ribosylation in regulating DNA interstrand crosslink repair and redundancy of this pathway with non-homologous end-joining (NHEJ). In silico searches were used to identify a protein that contains a permutated macrodomain (which we call aprataxin/APLF-and-PNKP-like protein; APL). Structural analysis reveals that this permutated macrodomain retains features associated with ADP-ribose interactions and that APL is capable of binding poly(ADP-ribose) through this macrodomain. APL is enriched in chromatin in response to cisplatin treatment, an agent that induces DNA interstrand crosslinks (ICLs). This is dependent on the macrodomain of APL and the ART Adprt2, indicating a role for ADP-ribosylation in the cellular response to cisplatin. Although adprt2− cells are sensitive to cisplatin, ADP-ribosylation is evident in these cells owing to redundant signalling by the double-strand break (DSB)-responsive ART Adprt1a, promoting NHEJ-mediated repair. These data implicate ADP-ribosylation in DNA ICL repair and identify that NHEJ can function to resolve this form of DNA damage in the absence of Adprt2. PMID:27587838

On testing for spatial correspondence between maps of human brain structure and function.

PubMed

Alexander-Bloch, Aaron F; Shou, Haochang; Liu, Siyuan; Satterthwaite, Theodore D; Glahn, David C; Shinohara, Russell T; Vandekar, Simon N; Raznahan, Armin

2018-06-01

A critical issue in many neuroimaging studies is the comparison between brain maps. Nonetheless, it remains unclear how one should test hypotheses focused on the overlap or spatial correspondence between two or more brain maps. This "correspondence problem" affects, for example, the interpretation of comparisons between task-based patterns of functional activation, resting-state networks or modules, and neuroanatomical landmarks. To date, this problem has been addressed with remarkable variability in terms of methodological approaches and statistical rigor. In this paper, we address the correspondence problem using a spatial permutation framework to generate null models of overlap by applying random rotations to spherical representations of the cortical surface, an approach for which we also provide a theoretical statistical foundation. We use this method to derive clusters of cognitive functions that are correlated in terms of their functional neuroatomical substrates. In addition, using publicly available data, we formally demonstrate the correspondence between maps of task-based functional activity, resting-state fMRI networks and gyral-based anatomical landmarks. We provide open-access code to implement the methods presented for two commonly-used tools for surface based cortical analysis (https://www.github.com/spin-test). This spatial permutation approach constitutes a useful advance over widely-used methods for the comparison of cortical maps, thereby opening new possibilities for the integration of diverse neuroimaging data. Copyright © 2018 Elsevier Inc. All rights reserved.

Sorting points into neighborhoods (SPIN): data analysis and visualization by ordering distance matrices.

PubMed

Tsafrir, D; Tsafrir, I; Ein-Dor, L; Zuk, O; Notterman, D A; Domany, E

2005-05-15

We introduce a novel unsupervised approach for the organization and visualization of multidimensional data. At the heart of the method is a presentation of the full pairwise distance matrix of the data points, viewed in pseudocolor. The ordering of points is iteratively permuted in search of a linear ordering, which can be used to study embedded shapes. Several examples indicate how the shapes of certain structures in the data (elongated, circular and compact) manifest themselves visually in our permuted distance matrix. It is important to identify the elongated objects since they are often associated with a set of hidden variables, underlying continuous variation in the data. The problem of determining an optimal linear ordering is shown to be NP-Complete, and therefore an iterative search algorithm with O(n3) step-complexity is suggested. By using sorting points into neighborhoods, i.e. SPIN to analyze colon cancer expression data we were able to address the serious problem of sample heterogeneity, which hinders identification of metastasis related genes in our data. Our methodology brings to light the continuous variation of heterogeneity--starting with homogeneous tumor samples and gradually increasing the amount of another tissue. Ordering the samples according to their degree of contamination by unrelated tissue allows the separation of genes associated with irrelevant contamination from those related to cancer progression. Software package will be available for academic users upon request.

Phylogeny of the Vitamin K 2,3-Epoxide Reductase (VKOR) Family and Evolutionary Relationship to the Disulfide Bond Formation Protein B (DsbB) Family

PubMed Central

Bevans, Carville G.; Krettler, Christoph; Reinhart, Christoph; Watzka, Matthias; Oldenburg, Johannes

2015-01-01

In humans and other vertebrate animals, vitamin K 2,3-epoxide reductase (VKOR) family enzymes are the gatekeepers between nutritionally acquired K vitamins and the vitamin K cycle responsible for posttranslational modifications that confer biological activity upon vitamin K-dependent proteins with crucial roles in hemostasis, bone development and homeostasis, hormonal carbohydrate regulation and fertility. We report a phylogenetic analysis of the VKOR family that identifies five major clades. Combined phylogenetic and site-specific conservation analyses point to clade-specific similarities and differences in structure and function. We discovered a single-site determinant uniquely identifying VKOR homologs belonging to human pathogenic, obligate intracellular prokaryotes and protists. Building on previous work by Sevier et al. (Protein Science 14:1630), we analyzed structural data from both VKOR and prokaryotic disulfide bond formation protein B (DsbB) families and hypothesize an ancient evolutionary relationship between the two families where one family arose from the other through a gene duplication/deletion event. This has resulted in circular permutation of primary sequence threading through the four-helical bundle protein folds of both families. This is the first report of circular permutation relating distant α-helical membrane protein sequences and folds. In conclusion, we suggest a chronology for the evolution of the five extant VKOR clades. PMID:26230708

Altered resting-state connectivity within default mode network associated with late chronotype.

PubMed

Horne, Charlotte Mary; Norbury, Ray

2018-04-20

Current evidence suggests late chronotype individuals have an increased risk of developing depression. However, the underlying neural mechanisms of this association are not fully understood. Forty-six healthy, right-handed individuals free of current or previous diagnosis of depression, family history of depression or sleep disorder underwent resting-state functional Magnetic Resonance Imaging (rsFMRI). Using an Independent Component Analysis (ICA) approach, the Default Mode Network (DMN) was identified based on a well validated template. Linear effects of chronotype on DMN connectivity were tested for significance using non-parametric permutation tests (applying 5000 permutations). Sleep quality, age, gender, measures of mood and anxiety, time of scan and cortical grey matter volume were included as covariates in the regression model. A significant positive correlation between chronotype and functional connectivity within nodes of the DMN was observed, including; bilateral PCC and precuneus, such that later chronotype (participants with lower rMEQ scores) was associated with decreased connectivity within these regions. The current results appear consistent with altered DMN connectivity in depressed patients and weighted evidence towards reduced DMN connectivity in other at-risk populations which may, in part, explain the increased vulnerability for depression in late chronotype individuals. The effect may be driven by self-critical thoughts associated with late chronotype although future studies are needed to directly investigate this. Copyright © 2018 Elsevier Ltd. All rights reserved.

Permutation entropy of finite-length white-noise time series.

PubMed

Little, Douglas J; Kane, Deb M

2016-08-01

Permutation entropy (PE) is commonly used to discriminate complex structure from white noise in a time series. While the PE of white noise is well understood in the long time-series limit, analysis in the general case is currently lacking. Here the expectation value and variance of white-noise PE are derived as functions of the number of ordinal pattern trials, N, and the embedding dimension, D. It is demonstrated that the probability distribution of the white-noise PE converges to a χ^{2} distribution with D!-1 degrees of freedom as N becomes large. It is further demonstrated that the PE variance for an arbitrary time series can be estimated as the variance of a related metric, the Kullback-Leibler entropy (KLE), allowing the qualitative N≫D! condition to be recast as a quantitative estimate of the N required to achieve a desired PE calculation precision. Application of this theory to statistical inference is demonstrated in the case of an experimentally obtained noise series, where the probability of obtaining the observed PE value was calculated assuming a white-noise time series. Standard statistical inference can be used to draw conclusions whether the white-noise null hypothesis can be accepted or rejected. This methodology can be applied to other null hypotheses, such as discriminating whether two time series are generated from different complex system states.

Phylogeny of the Vitamin K 2,3-Epoxide Reductase (VKOR) Family and Evolutionary Relationship to the Disulfide Bond Formation Protein B (DsbB) Family.

PubMed

Bevans, Carville G; Krettler, Christoph; Reinhart, Christoph; Watzka, Matthias; Oldenburg, Johannes

2015-07-29

In humans and other vertebrate animals, vitamin K 2,3-epoxide reductase (VKOR) family enzymes are the gatekeepers between nutritionally acquired K vitamins and the vitamin K cycle responsible for posttranslational modifications that confer biological activity upon vitamin K-dependent proteins with crucial roles in hemostasis, bone development and homeostasis, hormonal carbohydrate regulation and fertility. We report a phylogenetic analysis of the VKOR family that identifies five major clades. Combined phylogenetic and site-specific conservation analyses point to clade-specific similarities and differences in structure and function. We discovered a single-site determinant uniquely identifying VKOR homologs belonging to human pathogenic, obligate intracellular prokaryotes and protists. Building on previous work by Sevier et al. (Protein Science 14:1630), we analyzed structural data from both VKOR and prokaryotic disulfide bond formation protein B (DsbB) families and hypothesize an ancient evolutionary relationship between the two families where one family arose from the other through a gene duplication/deletion event. This has resulted in circular permutation of primary sequence threading through the four-helical bundle protein folds of both families. This is the first report of circular permutation relating distant a-helical membrane protein sequences and folds. In conclusion, we suggest a chronology for the evolution of the five extant VKOR clades.

Comparison of permutationally invariant polynomials, neural networks, and Gaussian approximation potentials in representing water interactions through many-body expansions

NASA Astrophysics Data System (ADS)

Nguyen, Thuong T.; Székely, Eszter; Imbalzano, Giulio; Behler, Jörg; Csányi, Gábor; Ceriotti, Michele; Götz, Andreas W.; Paesani, Francesco

2018-06-01

The accurate representation of multidimensional potential energy surfaces is a necessary requirement for realistic computer simulations of molecular systems. The continued increase in computer power accompanied by advances in correlated electronic structure methods nowadays enables routine calculations of accurate interaction energies for small systems, which can then be used as references for the development of analytical potential energy functions (PEFs) rigorously derived from many-body (MB) expansions. Building on the accuracy of the MB-pol many-body PEF, we investigate here the performance of permutationally invariant polynomials (PIPs), neural networks, and Gaussian approximation potentials (GAPs) in representing water two-body and three-body interaction energies, denoting the resulting potentials PIP-MB-pol, Behler-Parrinello neural network-MB-pol, and GAP-MB-pol, respectively. Our analysis shows that all three analytical representations exhibit similar levels of accuracy in reproducing both two-body and three-body reference data as well as interaction energies of small water clusters obtained from calculations carried out at the coupled cluster level of theory, the current gold standard for chemical accuracy. These results demonstrate the synergy between interatomic potentials formulated in terms of a many-body expansion, such as MB-pol, that are physically sound and transferable, and machine-learning techniques that provide a flexible framework to approximate the short-range interaction energy terms.

Effects of geoduck (Panopea generosa) aquaculture on resident and transient macrofauna communities of Puget Sound, Washington, USA

USGS Publications Warehouse

Mcdonald, P. Sean; Galloway, Aaron W.E.; McPeek, Kathleen C.; VanBlaricom, Glenn R.

2015-01-01

In Washington state, commercial culture of geoducks (Panopea generosa) involves large-scale out-planting of juveniles to intertidal habitats, and installation of PVC tubes and netting to exclude predators and increase early survival. Structures associated with this nascent aquaculture method are examined to determine whether they affect patterns of use by resident and transient macrofauna. Results are summarized from regular surveys of aquaculture operations and reference beaches in 2009 to 2011 at three sites during three phases of culture: (1) pregear (-geoducks, -structure), (2) gear present (+geoducks, +structures), and (3) postgear (+geoducks, -structures). Resident macroinvertebrates (infauna and epifauna) were sampled monthly (in most cases) using coring methods at low tide during all three phases. Differences in community composition between culture plots and reference areas were examined with permutational analysis of variance and homogeneity of multivariate dispersion tests. Scuba and shoreline transect surveys were used to examine habitat use by transient fish and macroinvertebrates. Analysis of similarity and complementary nonmetric multidimensional scaling were used to compare differences between species functional groups and habitat type during different aquaculture phases. Results suggest that resident and transient macrofauna respond differently to structures associated with geoduck aquaculture. No consistent differences in the community of resident macrofauna were observed at culture plots or reference areas at the three sites during any year. Conversely, total abundance of transient fish and macroinvertebrates were more than two times greater at culture plots than reference areas when aquaculture structures were in place. Community composition differed (analysis of similarity) between culture and reference plots during the gear-present phase, but did not persist to the next farming stage (postgear). Habitat complexity associated with shellfish aquaculture may attract some structure-associated transient species observed infrequently on reference beaches, and may displace other species that typically occur in areas lacking epibenthic structure. This study provides a first look at the effects of multiple phases of geoduck farming on macrofauna, and has important implications for the management of a rapidly expanding sector of the aquaculture industry.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Orlenko, E. V., E-mail: eorlenko@mail.ru; Evstafev, A. V.; Orlenko, F. E.

A formalism of exchange perturbation theory (EPT) is developed for the case of interactions that explicitly depend on time. Corrections to the wave function obtained in any order of perturbation theory and represented in an invariant form include exchange contributions due to intercenter electron permutations in complex multicenter systems. For collisions of atomic systems with an arbitrary type of interaction, general expressions are obtained for the transfer (T) and scattering (S) matrices in which intercenter electron permutations between overlapping nonorthogonal states belonging to different centers (atoms) are consistently taken into account. The problem of collision of alpha particles with lithiummore » atoms accompanied by the redistribution of electrons between centers is considered. The differential and total charge-exchange cross sections of lithium are calculated.« less

Optimal recombination in genetic algorithms for flowshop scheduling problems

NASA Astrophysics Data System (ADS)

Kovalenko, Julia

2016-10-01

The optimal recombination problem consists in finding the best possible offspring as a result of a recombination operator in a genetic algorithm, given two parent solutions. We prove NP-hardness of the optimal recombination for various variants of the flowshop scheduling problem with makespan criterion and criterion of maximum lateness. An algorithm for solving the optimal recombination problem for permutation flowshop problems is built, using enumeration of prefect matchings in a special bipartite graph. The algorithm is adopted for the classical flowshop scheduling problem and for the no-wait flowshop problem. It is shown that the optimal recombination problem for the permutation flowshop scheduling problem is solvable in polynomial time for almost all pairs of parent solutions as the number of jobs tends to infinity.

Multivariate calibration in Laser-Induced Breakdown Spectroscopy quantitative analysis: The dangers of a 'black box' approach and how to avoid them

NASA Astrophysics Data System (ADS)

Safi, A.; Campanella, B.; Grifoni, E.; Legnaioli, S.; Lorenzetti, G.; Pagnotta, S.; Poggialini, F.; Ripoll-Seguer, L.; Hidalgo, M.; Palleschi, V.

2018-06-01

The introduction of multivariate calibration curve approach in Laser-Induced Breakdown Spectroscopy (LIBS) quantitative analysis has led to a general improvement of the LIBS analytical performances, since a multivariate approach allows to exploit the redundancy of elemental information that are typically present in a LIBS spectrum. Software packages implementing multivariate methods are available in the most diffused commercial and open source analytical programs; in most of the cases, the multivariate algorithms are robust against noise and operate in unsupervised mode. The reverse of the coin of the availability and ease of use of such packages is the (perceived) difficulty in assessing the reliability of the results obtained which often leads to the consideration of the multivariate algorithms as 'black boxes' whose inner mechanism is supposed to remain hidden to the user. In this paper, we will discuss the dangers of a 'black box' approach in LIBS multivariate analysis, and will discuss how to overcome them using the chemical-physical knowledge that is at the base of any LIBS quantitative analysis.

Linear regression analysis and its application to multivariate chromatographic calibration for the quantitative analysis of two-component mixtures.

PubMed

Dinç, Erdal; Ozdemir, Abdil

2005-01-01

Multivariate chromatographic calibration technique was developed for the quantitative analysis of binary mixtures enalapril maleate (EA) and hydrochlorothiazide (HCT) in tablets in the presence of losartan potassium (LST). The mathematical algorithm of multivariate chromatographic calibration technique is based on the use of the linear regression equations constructed using relationship between concentration and peak area at the five-wavelength set. The algorithm of this mathematical calibration model having a simple mathematical content was briefly described. This approach is a powerful mathematical tool for an optimum chromatographic multivariate calibration and elimination of fluctuations coming from instrumental and experimental conditions. This multivariate chromatographic calibration contains reduction of multivariate linear regression functions to univariate data set. The validation of model was carried out by analyzing various synthetic binary mixtures and using the standard addition technique. Developed calibration technique was applied to the analysis of the real pharmaceutical tablets containing EA and HCT. The obtained results were compared with those obtained by classical HPLC method. It was observed that the proposed multivariate chromatographic calibration gives better results than classical HPLC.

Multivariate analysis: A statistical approach for computations

NASA Astrophysics Data System (ADS)

Michu, Sachin; Kaushik, Vandana

2014-10-01

Multivariate analysis is a type of multivariate statistical approach commonly used in, automotive diagnosis, education evaluating clusters in finance etc and more recently in the health-related professions. The objective of the paper is to provide a detailed exploratory discussion about factor analysis (FA) in image retrieval method and correlation analysis (CA) of network traffic. Image retrieval methods aim to retrieve relevant images from a collected database, based on their content. The problem is made more difficult due to the high dimension of the variable space in which the images are represented. Multivariate correlation analysis proposes an anomaly detection and analysis method based on the correlation coefficient matrix. Anomaly behaviors in the network include the various attacks on the network like DDOs attacks and network scanning.

Multivariate Cluster Analysis.

ERIC Educational Resources Information Center

McRae, Douglas J.

Procedures for grouping students into homogeneous subsets have long interested educational researchers. The research reported in this paper is an investigation of a set of objective grouping procedures based on multivariate analysis considerations. Four multivariate functions that might serve as criteria for adequate grouping are given and…

HLA-DRB1 rheumatoid arthritis risk in African Americans at multiple levels: Hierarchical classification systems, amino acid positions and residues

PubMed Central

Reynolds, Richard J.; Ahmed, Altan F.; Danila, Maria I.; Hughes, Laura B.; Gregersen, Peter K.; Raychaudhuri, Soumya; Plenge, Robert M.; Bridges, S. Louis

2014-01-01

Objective To evaluate African American rheumatoid arthritis HLA-DRB1 genetic risk by three validated allele classification systems, and by amino acid position and residue. To compare the genetic risk between African American and European ancestries. Methods Four-digit HLA-DRB1 genotyping was performed on 561 autoantibody-positive African American cases and 776 African American controls. Association analysis was performed on Tezenas du Montcel (TdM); de Vries (DV); and Mattey classification system alleles and separately by amino acid position and individual residues. Results TdM S2 and S3P alleles were associated with RA (odds ratios (95% CI) 2.8 (2.0, 3.9) and 2.1 (1.7, 2.7), respectively). The DV (P-value=3.2 x 10−12) and Mattey (P-value=6.5 x 10−13) system alleles were both protective in African Americans. Amino acid position 11 (permutation P-value < 0.00001) accounted for nearly all variability explained by HLA-DRB1, although conditional analysis demonstrated that position 57 was also significant (0.01<= permutation P-val <=0.05). The valine and aspartic acid residues at position 11 conferred the highest risk for RA in African Americans. Conclusion With some exceptions, the genetic risk conferred by HLA-DRB1 in African Americans is similar to European ancestry at multiple levels: classification system (e.g., TdM), amino acid position (e.g. 11) and residue (Val 11). Unlike that reported from European ancestry, amino acid position 57 was associated with RA in African Americans, but positions 71 and 74 were not. Asp11 (OR = 1 in European ancestry) corresponds to the four digit classical allele, *09:01, also a risk allele for RA in Koreans. PMID:25524867

Spectral Dynamics of Resting State fMRI Within the Ventral Tegmental Area and Dorsal Raphe Nuclei in Medication-Free Major Depressive Disorder in Young Adults.

PubMed

Wohlschläger, Afra; Karne, Harish; Jordan, Denis; Lowe, Mark J; Jones, Stephen E; Anand, Amit

2018-01-01

Background: Dorsal raphe nucleus (DRN) and ventral tegmental area (VTA) are major brainstem monamine nuclei consisting of serotonin and dopamine neurons respectively. Animal studies show that firing patterns in both nuclei are altered when animals exhibit depression like behaviors. Functional MRI studies in humans have shown reduced VTA activation and DRN connectivity in depression. This study for the first time aims at investigating the functional integrity of local neuronal firing concurrently in both the VTA and DRN in vivo in humans using spectral analysis of resting state low frequency fluctuation fMRI. Method: A total of 97 medication-free subjects-67 medication-free young patients (ages 18-30) with major depressive disorder and 30 closely matched healthy controls were included in the study to detect aberrant dynamics in DRN and VTA. For the investigation of altered localized dynamics we conducted power spectral analysis and above this spectral cross correlation between the two groups. Complementary to this, spectral dependence of permutation entropy, an information theoretical measure, was compared between groups. Results: Patients displayed significant spectral slowing in VTA vs. controls ( p = 0.035, corrected). In DRN, spectral slowing was less pronounced, but the amount of slowing significantly correlated with 17-item Hamilton Depression Rating scores of depression severity ( p = 0.038). Signal complexity as assessed via permutation entropy showed spectral alterations inline with the results on spectral slowing. Conclusion: Our results indicate that altered functional dynamics of VTA and DRN in depression can be detected from regional fMRI signal. On this basis, impact of antidepressant treatment and treatment response can be assessed using these markers in future studies.

The Genome-Wide Influence on Human BMI Depends on Physical Activity, Life Course, and Historical Period.

PubMed

Guo, Guang; Liu, Hexuan; Wang, Ling; Shen, Haipeng; Hu, Wen

2015-10-01

In this analysis, guided by an evolutionary framework, we investigate how the human genome as a whole interacts with historical period, age, and physical activity to influence body mass index (BMI). The genomic influence is estimated by (1) heritability or the proportion of variance in BMI explained by genome-wide genotype data, and (2) the random effects or the best linear unbiased predictors (BLUPs) of genome-wide association studies (GWAS) data on BMI. Data were used from the Framingham Heart Study (FHS) in the United States. The study was initiated in 1948, and the obesity data were collected repeatedly over the subsequent decades. The analyses draw analysis samples from a pool of >8,000 individuals in the FHS. The hypothesis testing based on Pitman test, permutation Pitman test, F test, and permutation F test produces three sets of significant findings. First, the genomic influence on BMI is substantially larger after the mid-1980s than in the few decades before the mid-1980s within each age group of 21-40, 41-50, 51-60, and >60. Second, the genomic influence on BMI weakens as one ages across the life course, or the genomic influence on BMI tends to be more important during reproductive ages than after reproductive ages within each of the two historical periods. Third, within the age group of 21-50 and not in the age group of >50, the genomic influence on BMI among physically active individuals is substantially smaller than the influence on those who are not physically active. In summary, this study provides evidence that the influence of human genome as a whole on obesity depends on historical period, age, and level of physical activity.

Atypical nucleus accumbens morphology in psychopathy: another limbic piece in the puzzle.

PubMed

Boccardi, Marina; Bocchetta, Martina; Aronen, Hannu J; Repo-Tiihonen, Eila; Vaurio, Olli; Thompson, Paul M; Tiihonen, Jari; Frisoni, Giovanni B

2013-01-01

Psychopathy has been associated with increased putamen and striatum volumes. The nucleus accumbens - a key structure in reversal learning, less effective in psychopathy - has not yet received specific attention. Moreover, basal ganglia morphology has never been explored. We examined the morphology of the caudate, putamen and accumbens, manually segmented from magnetic resonance images of 26 offenders (age: 32.5 ± 8.4) with medium-high psychopathy (mean PCL-R=30 ± 5) and 25 healthy controls (age: 34.6 ± 10.8). Local differences were statistically modeled using a surface-based radial distance mapping method (p<0.05; multiple comparisons correction through permutation tests). In psychopathy, the caudate and putamen had normal global volume, but different morphology, significant after correction for multiple comparisons, for the right dorsal putamen (permutation test: p=0.02). The volume of the nucleus accumbens was 13% smaller in psychopathy (p corrected for multiple comparisons <0.006). The atypical morphology consisted of predominant anterior hypotrophy bilaterally (10-30%). Caudate and putamen local morphology displayed negative correlation with the lifestyle factor of the PCL-R (permutation test: p=0.05 and 0.03). From these data, psychopathy appears to be associated with an atypical striatal morphology, with highly significant global and local differences of the accumbens. This is consistent with the clinical syndrome and with theories of limbic involvement. Copyright © 2013 Elsevier Ltd. All rights reserved.

A secure transmission scheme of streaming media based on the encrypted control message

NASA Astrophysics Data System (ADS)

Li, Bing; Jin, Zhigang; Shu, Yantai; Yu, Li

2007-09-01

As the use of streaming media applications increased dramatically in recent years, streaming media security becomes an important presumption, protecting the privacy. This paper proposes a new encryption scheme in view of characteristics of streaming media and the disadvantage of the living method: encrypt the control message in the streaming media with the high security lever and permute and confuse the data which is non control message according to the corresponding control message. Here the so-called control message refers to the key data of the streaming media, including the streaming media header and the header of the video frame, and the seed key. We encrypt the control message using the public key encryption algorithm which can provide high security lever, such as RSA. At the same time we make use of the seed key to generate key stream, from which the permutation list P responding to GOP (group of picture) is derived. The plain text of the non-control message XORs the key stream and gets the middle cipher text. And then obtained one is permutated according to P. In contrast the decryption process is the inverse process of the above. We have set up a testbed for the above scheme and found our scheme is six to eight times faster than the conventional method. It can be applied not only between PCs but also between handheld devices.

Spectral and cross-spectral analysis of uneven time series with the smoothed Lomb-Scargle periodogram and Monte Carlo evaluation of statistical significance

NASA Astrophysics Data System (ADS)

Pardo-Igúzquiza, Eulogio; Rodríguez-Tovar, Francisco J.

2012-12-01

Many spectral analysis techniques have been designed assuming sequences taken with a constant sampling interval. However, there are empirical time series in the geosciences (sediment cores, fossil abundance data, isotope analysis, …) that do not follow regular sampling because of missing data, gapped data, random sampling or incomplete sequences, among other reasons. In general, interpolating an uneven series in order to obtain a succession with a constant sampling interval alters the spectral content of the series. In such cases it is preferable to follow an approach that works with the uneven data directly, avoiding the need for an explicit interpolation step. The Lomb-Scargle periodogram is a popular choice in such circumstances, as there are programs available in the public domain for its computation. One new computer program for spectral analysis improves the standard Lomb-Scargle periodogram approach in two ways: (1) It explicitly adjusts the statistical significance to any bias introduced by variance reduction smoothing, and (2) it uses a permutation test to evaluate confidence levels, which is better suited than parametric methods when neighbouring frequencies are highly correlated. Another novel program for cross-spectral analysis offers the advantage of estimating the Lomb-Scargle cross-periodogram of two uneven time series defined on the same interval, and it evaluates the confidence levels of the estimated cross-spectra by a non-parametric computer intensive permutation test. Thus, the cross-spectrum, the squared coherence spectrum, the phase spectrum, and the Monte Carlo statistical significance of the cross-spectrum and the squared-coherence spectrum can be obtained. Both of the programs are written in ANSI Fortran 77, in view of its simplicity and compatibility. The program code is of public domain, provided on the website of the journal (http://www.iamg.org/index.php/publisher/articleview/frmArticleID/112/). Different examples (with simulated and real data) are described in this paper to corroborate the methodology and the implementation of these two new programs.

Comparative forensic soil analysis of New Jersey state parks using a combination of simple techniques with multivariate statistics.

PubMed

Bonetti, Jennifer; Quarino, Lawrence

2014-05-01

This study has shown that the combination of simple techniques with the use of multivariate statistics offers the potential for the comparative analysis of soil samples. Five samples were obtained from each of twelve state parks across New Jersey in both the summer and fall seasons. Each sample was examined using particle-size distribution, pH analysis in both water and 1 M CaCl2 , and a loss on ignition technique. Data from each of the techniques were combined, and principal component analysis (PCA) and canonical discriminant analysis (CDA) were used for multivariate data transformation. Samples from different locations could be visually differentiated from one another using these multivariate plots. Hold-one-out cross-validation analysis showed error rates as low as 3.33%. Ten blind study samples were analyzed resulting in no misclassifications using Mahalanobis distance calculations and visual examinations of multivariate plots. Seasonal variation was minimal between corresponding samples, suggesting potential success in forensic applications. © 2014 American Academy of Forensic Sciences.

Quantifying the impact of between-study heterogeneity in multivariate meta-analyses

PubMed Central

Jackson, Dan; White, Ian R; Riley, Richard D

2012-01-01

Measures that quantify the impact of heterogeneity in univariate meta-analysis, including the very popular I2 statistic, are now well established. Multivariate meta-analysis, where studies provide multiple outcomes that are pooled in a single analysis, is also becoming more commonly used. The question of how to quantify heterogeneity in the multivariate setting is therefore raised. It is the univariate R2 statistic, the ratio of the variance of the estimated treatment effect under the random and fixed effects models, that generalises most naturally, so this statistic provides our basis. This statistic is then used to derive a multivariate analogue of I2, which we call . We also provide a multivariate H2 statistic, the ratio of a generalisation of Cochran's heterogeneity statistic and its associated degrees of freedom, with an accompanying generalisation of the usual I2 statistic, . Our proposed heterogeneity statistics can be used alongside all the usual estimates and inferential procedures used in multivariate meta-analysis. We apply our methods to some real datasets and show how our statistics are equally appropriate in the context of multivariate meta-regression, where study level covariate effects are included in the model. Our heterogeneity statistics may be used when applying any procedure for fitting the multivariate random effects model. Copyright © 2012 John Wiley & Sons, Ltd. PMID:22763950

Analyzing Multiple Outcomes in Clinical Research Using Multivariate Multilevel Models

PubMed Central

Baldwin, Scott A.; Imel, Zac E.; Braithwaite, Scott R.; Atkins, David C.

2014-01-01

Objective Multilevel models have become a standard data analysis approach in intervention research. Although the vast majority of intervention studies involve multiple outcome measures, few studies use multivariate analysis methods. The authors discuss multivariate extensions to the multilevel model that can be used by psychotherapy researchers. Method and Results Using simulated longitudinal treatment data, the authors show how multivariate models extend common univariate growth models and how the multivariate model can be used to examine multivariate hypotheses involving fixed effects (e.g., does the size of the treatment effect differ across outcomes?) and random effects (e.g., is change in one outcome related to change in the other?). An online supplemental appendix provides annotated computer code and simulated example data for implementing a multivariate model. Conclusions Multivariate multilevel models are flexible, powerful models that can enhance clinical research. PMID:24491071

A Spectral Algorithm for Envelope Reduction of Sparse Matrices

NASA Technical Reports Server (NTRS)

Barnard, Stephen T.; Pothen, Alex; Simon, Horst D.

1993-01-01

The problem of reordering a sparse symmetric matrix to reduce its envelope size is considered. A new spectral algorithm for computing an envelope-reducing reordering is obtained by associating a Laplacian matrix with the given matrix and then sorting the components of a specified eigenvector of the Laplacian. This Laplacian eigenvector solves a continuous relaxation of a discrete problem related to envelope minimization called the minimum 2-sum problem. The permutation vector computed by the spectral algorithm is a closest permutation vector to the specified Laplacian eigenvector. Numerical results show that the new reordering algorithm usually computes smaller envelope sizes than those obtained from the current standard algorithms such as Gibbs-Poole-Stockmeyer (GPS) or SPARSPAK reverse Cuthill-McKee (RCM), in some cases reducing the envelope by more than a factor of two.

Tag-KEM from Set Partial Domain One-Way Permutations

NASA Astrophysics Data System (ADS)

Abe, Masayuki; Cui, Yang; Imai, Hideki; Kurosawa, Kaoru

Recently a framework called Tag-KEM/DEM was introduced to construct efficient hybrid encryption schemes. Although it is known that generic encode-then-encrypt construction of chosen ciphertext secure public-key encryption also applies to secure Tag-KEM construction and some known encoding method like OAEP can be used for this purpose, it is worth pursuing more efficient encoding method dedicated for Tag-KEM construction. This paper proposes an encoding method that yields efficient Tag-KEM schemes when combined with set partial one-way permutations such as RSA and Rabin's encryption scheme. To our knowledge, this leads to the most practical hybrid encryption scheme of this type. We also present an efficient Tag-KEM which is CCA-secure under general factoring assumption rather than Blum factoring assumption.